Comprehensive analysis of normal adjacent to tumor transcriptomes

3'UTR RNA editing driven by ADAR1 modulates MDM2 expression in breast cancer cells

Epitranscriptomic changes in the transcripts of cancer related genes could modulate protein levels. RNA editing, particularly A-to-I(G) editing catalyzed by ADAR1, has been implicated in cancer progression. RNA editing events in the 3' untranslated region (3'UTR) can regulate mRNA stability, localization, and translation, underscoring the importance of exploring their impact in cancer. Here, we performed an in silico analysis to detect breast cancer enriched RNA editing sites using the TCGA breast cancer RNA-seq dataset. Notably, the majority of differential editing events mapped to 3' untranslated regions (3'UTRs). We confirmed A-to-I(G) editing in the 3'UTRs of MDM2 (Mouse Double Minute 2 homolog), GINS1 (GINS Complex Subunit 1), and F11R (Junctional Adhesion Molecule A) in breast cancer cells. RNA immunoprecipitation with ADAR1 antibody confirmed the interaction between ADAR1 and MDM2, GINS1, and F11R 3'UTRs. ADAR1 knockdown revealed decreased editing levels, establishing ADAR1 as the editing enzyme. A reporter assay for MDM2, an oncogene overexpressed mostly in luminal breast cancers, demonstrated that RNA editing enhances protein expression, in agreement with reduced MDM2 protein levels in ADAR1 knockdown cells. Further exploration into the mechanisms of 3'UTR editing events revealed an interaction between ADAR1 and CSTF2, a core component of the polyadenylation machinery, as identified through biotin-based proximity labeling mass spectroscopy, and co-immunoprecipitation experiments. Furthermore, CSTF2 knockdown reduced both ADAR1 and MDM2 protein levels. Our findings highlight implications for MDM2 regulation by ADAR1-dependent 3'UTR RNA editing and present an interplay between RNA editing on 3'UTRs and the mRNA polyadenylation machinery. These results improve our understanding of ADAR1's role in cancer-associated 3' UTR RNA editing and its potential as a therapeutic target.

The EGFR Pathway as a Potential Therapeutic Target for Modulation of Radiation-induced Liver Injury

Radiation exposure can result in various complications influenced by factors such as dose, the amount of tissue exposed, and the type of tissue exposed. Radiation-induced liver injury (RILI) is a concern in cancer patients receiving thoracic and upper abdominal radiation, but it can also be a risk for civilians exposed to radiation in a nuclear event. RILI can lead to organ dysfunction or death; a deeper understanding of how radiation causes damage to normal tissue could pave the way for new treatments. In our study, we focused on the effects of radiation on the two main liver cell types: liver sinusoidal endothelial cells (LSECs) and hepatocytes. We exposed these cells to different doses of radiation (2, 4 or 8 Gy) as well as a sham irradiation (0 Gy) control. Proteins were extracted at 30 min, 6 h and 24 h postirradiation and analyzed using reverse phase protein array (RPPA). We observed changes to the Hepatic fibrosis signaling pathway, IL-8 signaling, and S100 family signaling pathways across multiple doses and time points in LSECs. In hepatocytes, radiation affected different pathways; we see changes in the Th1 and Th2 signaling pathways and the IL-10 signaling pathway. These pathways are critical in mediating the immune response, with Th1 being associated with pro-inflammatory responses and Th2 with anti-inflammatory responses. Hub proteins from protein-protein interaction (PPI) networks across all time points for both LSECs and hepatocytes highlighted EGFR as a top-ranked protein, indicating the potential role in mitigating radiation damage in liver cells. Herein, we showed alterations in protein expression after RILI using RPPA at early time points (hours to days) to determine potentially targetable molecular pathways. We further highlighted potential therapeutic protein markers, including EGFR, as an example of the potential utility of RPPA in target discovery.

Multisite long-read sequencing reveals the early contributions of somatic structural variations to HBV-related hepatocellular carcinoma tumorigenesis

Somatic structural variations (SVs) represent a critical category of genomic mutations in hepatocellular carcinoma (HCC). However, the accurate identification of somatic SVs using short-read high-throughput sequencing is challenging. Here, we applied long-read nanopore sequencing and multisite sampling in a cohort of 42 samples from five patients. We found that adjacent nontumor tissue is not entirely normal, as significant somatic SV alterations were detected in these nontumor genomes. The adjacent nontumor tissue is highly similar to tumor tissue in terms of somatic SVs but differs in somatic single-nucleotide variants and copy number variations. The types of SVs in adjacent nontumor and tumor tissue are markedly different, with somatic insertions and deletions identified as early genomic events associated with HCC. Notably, hepatitis B virus (HBV) DNA integration frequently results in the generation of somatic SVs, particularly inducing interchromosomal translocations (TRAs). Although HBV DNA integration into the liver genome occurs randomly, multisite shared HBV-induced SVs are early driving events in the pathogenesis of HCC. Long-read RNA sequencing reveals that some HBV-induced SVs impact cancer-associated genes, with TRAs being capable of inducing the formation of fusion genes. These findings enhance our understanding of somatic SVs in HCC and their role in early tumorigenesis.

Global profiling of alternative splicing in non-small cell lung cancer reveals novel histological and population differences

Lung cancer is one of the most frequently diagnosed cancers in the US. African-American (AA) men are more likely to develop lung cancer with higher incidence and mortality rates than European-American (EA) men. Herein, we report high-confidence alternative splicing (AS) events from high-throughput, high-depth total RNA sequencing of lung tumors and non-tumor adjacent tissues (NATs) in two independent cohorts of patients with adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). We identified novel AS biomarkers with notable differential percent spliced in (PSI) values between lung tumors and NATs enriched in the AA and EA populations, which were associated with oncogenic signaling pathways. We also uncovered tumor subtype- and population-specific AS events associated with cell surface proteins and cancer driver genes. We highlighted significant AS events in SYNE2 specific to LUAD in both populations, as well as those in CD44 from EAs and TMBIM6 from AAs specific to LUAD. Here, we also present the validation of cancer signatures based on direct high-throughput reverse transcription-PCR. Our large survey of lung tumors presents a rich data resource that may help to understand molecular subtypes of lung tumor between AAs and EAs and reveal new therapeutic vulnerabilities that potentially advance health equity.

Aging shapes infection profiles of influenza A virus and SARS-CoV-2 in human precision-cut lung slices

BACKGROUND

The coronavirus disease 2019 (COVID-19) outbreak revealed the susceptibility of elderly patients to respiratory virus infections, showing cell senescence or subclinical persistent inflammatory profiles and favoring the development of severe pneumonia.

METHODS

In our study, we evaluated the potential influence of lung aging on the efficiency of replication of influenza A virus (IAV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as well as determining the pro-inflammatory and antiviral responses of the distal lung tissue.

RESULTS

Using precision-cut lung slices (PCLS) from donors of different ages, we found that pandemic H1N1 and avian H5N1 IAV replicated in the lung parenchyma with high efficacy. In contrast to these IAV strains, SARS-CoV-2 Early isolate and Delta variant of concern (VOC) replicated less efficiently in PCLS. Interestingly, both viruses showed reduced replication in PCLS from older compared to younger donors, suggesting that aged lung tissue represents a suboptimal environment for viral replication. Regardless of the age-dependent viral loads, PCLS responded to H5N1 IAV infection by an induction of IL-6 and IP10/CXCL10, both at the mRNA and protein levels, and to H1N1 IAV infection by induction of IP10/CXCL10 mRNA. Finally, while SARS-CoV-2 and H1N1 IAV infection were not causing detectable cell death, H5N1 IAV infection led to more cytotoxicity and induced significant early interferon responses.

CONCLUSIONS

In summary, our findings suggest that aged lung tissue might not favor viral dissemination, pointing to a determinant role of dysregulated immune mechanisms in the development of severe disease.

Developing a gene expression classifier for breast cancer diagnosis

Breast cancer (BC) is the most common type of cancer in women worldwide. Solid tumors are complex structures composed of many cell types and extracellular matrix components. Understanding solid tumors is crucial for developing effective treatments. This study aimed to develop a gene expression classifier to predict BC with high accuracy. The study first identified the most important genes for cancer through differential expression analysis (DEA) between breast cancer and adjacent normal breast samples. The R package STRINGdb was then used to create a protein-protein interaction network (PPI) to examine upregulated genes and find clusters. Enrichment analyses were performed to identify overrepresented biological functions and pathways. A logistic regression prediction model was developed using a breast cancer dataset from TCGA and evaluated using discrimination and calibration measures. BUB1 expression in breast cancer was also investigated using quantitative analysis. Two significant clusters were identified, with cell cycle checkpoints and M phase key pathways in one cluster and extracellular matrix organization in the other. A prediction model using the hub gene set (COMP, FN1, SDC1, BUB1, TTK, and NUSAP1) showed high sensitivity (97.2%) and specificity (96.1%), and an AUC of 0.994. Three hub genes (COMP, FN1, and SDC1) were identified through the PPI network, strongly linked to extracellular matrix organization (BUB1, TTK, and NUSAP1) as hub genes involved in M phase and cell cycle checkpoints. Overall, the study identified hub pathways and genes that accurately distinguish between cancer and normal samples, presenting promising new possibilities for early cancer detection and improved BC therapy.

Tumor suppressor genes in the tumor microenvironment

Tumor suppressor genes (TSGs) are thought to suppress tumor development primarily via cancer cell-autonomous mechanisms. However, the tumor microenvironment (TME) also significantly influences tumorigenesis. In this context, a role for TSGs in the various cell types of the TME in regulating tumor growth is emerging. Indeed, expression analyses of TSGs in clinical samples, along with data from mouse models in which TSGs were deleted selectively in the TME, indicate a functional role for them in tumor development. In this Perspective, using TP53 and PTEN as examples, we posit that TSGs play a significant role in cells of the TME in regulating tumor development, and postulate both a 'pro-active' and 'reactive' model for their contribution to tumor growth, dependent on the temporal sequence of initiating events. Finally, we discuss the need to consider a 2-in-1 cancer-treatment strategy to improve the efficacy of clearance of cancer cells and the cancer-promoting TME.

Tumor metabolism as a factor affecting diversity in cancer cachexia

Cancer cachexia is a multifaceted metabolic syndrome characterized by muscle wasting, fat redistribution, and metabolic dysregulation, commonly associated with advanced cancer but sometimes also evident in early-stage disease. More subtle body composition changes have also been reported in association with cancer, including sarcopenia, myosteatosis, and increased fat radiodensity. Emerging evidence reveals that body composition changes including sarcopenia, myosteatosis, and increased fat radiodensity, arise from distinct biological mechanisms and significantly impact survival outcomes. Importantly, these features often occur independently, with their combined presence exacerbating poor prognoses. Tumor plays a pivotal role in driving these host changes, either by acting as a metabolic parasite or by releasing mediators that disrupt normal tissue function. This review explores the diversity of tumor metabolism. It highlights the potential for tumor-specific metabolic phenotypes to influence systemic effects, including fat redistribution and sarcopenia. Addressing this tumor-host metabolic interplay requires personalized approaches that disrupt tumor metabolism while preserving host health. Promising strategies include targeted pharmacological interventions and anticachexia agents like growth differentiation factor 15 (GDF-15) inhibitors. Nutritional modifications such as ketogenic diets and omega-3 fatty acid supplementation also merit further investigation. In addition to preserving muscle, these therapies will need to be evaluated for their capability to improve survival and quality of life. This review underscores the need for further research into tumor-driven metabolic effects on the host and the development of integrative treatment strategies to address the interconnected challenges of cancer progression and cachexia.

Temporal and Spatial Metabolic Shifts Revealing the Transition from Ulcerative Colitis to Colitis-Associated Colorectal Cancer

Patients with ulcerative colitis (UC) have a higher risk of developing colorectal cancer (CRC), however, the metabolic shifts during the UC-to-CRC transition remain elusive. In this study, an AOM-DSS-induced three-stage colitis-associated colorectal cancer (CAC) model is constructed and targeted metabolomics analysis and pathway enrichment are performed, uncovering the metabolic changes in this transition. Spatial metabolic trajectories in the "normal-to-normal adjacent tissue (NAT)-to-tumor" transition, and temporal metabolic trajectories in the "colitis-to-dysplasia-to-carcinoma" transition are identified through K-means clustering of 74 spatially and 77 temporally differential metabolites, respectively. The findings reveal two distinct metabolic profile categories during the inflammation-to-cancer progression: those with consistent changes, either increasing (e.g., kynurenic acid, xanthurenic acid) or decreasing (e.g., long-chain fatty acids, LCFAs), and those enriched at specific disease stages (e.g., serotonin). Further analysis of metabolites with consistent temporal trends identifies eicosapentaenoic acid (EPA) as a key metabolite, potentially exerting anti-inflammatory and anti-cancer effects by inhibiting insulin-like growth factor binding protein 5 (IGFBP5). This study reveals novel metabolic mechanisms underlying the transition from UC to CAC and suggests potential targets to delay the progression.

Intraneoplastic fungal dysbiosis is associated with colorectal cancer progression and host gene mutation

BACKGROUND

The relationship between intraneoplastic fungi and colorectal cancer (CRC) progression remains largely unclear. Here, we investigated fungal community changes in adenoma and CRC and their correlation with host genetic mutations.

METHODS

We obtained 261 tissue biopsies from two geographically distinct cohorts of CRC and adenoma patients, with each individual contributing 2-5 biopsies from lesions and 2 from adjacent normal tissues. 18S ribosomal RNA gene sequencing was used for microbial profiling. Host genetic alterations including KRAS mutations and microsatellite instability (MSI) were detected concurrently.

FINDINGS

Intra-neoplastic fungal composition significantly differed between CRC and adenoma in two independent cohorts, with enrichment of highly variable fungi (HVF) in CRC. Six HVFs exhibited higher abundances in adenoma and CRC compared to adjacent normal tissues with Malassezia showing a progressive increase from adenoma to CRC. Fungi intratumoral heterogeneity index also increased from adenoma through stages I to IV of CRC. Intra-tumoral fungi-fungi co-abundance analysis indicated stronger positive interactions in CRC than in adenoma, with increasingly robust links among intra-tumoral fungi along adenoma-CRC progression, primarily driven by Malassezia and Aspergillus. Furthermore, fungal heterogeneity was significantly correlated with host genetic mutations, with higher risk indices in CRC tissues harboring KRAS and MSI mutations. Thirteen fungi stratified CRC samples with KRAS mutations, achieving an area under the curve (AUC) of 0.86, while those associated with MSI status showed an AUC of 0.89.

INTERPRETATION

This study demonstrates that intraneoplastic fungal community alterations occur between adenoma and CRC, with increasing heterogeneity associated with host genetic mutations, emphasizing the role of fungal dysbiosis in CRC.

FUNDING

This work was supported by RGC Research Impact Fund Hong Kong (R4032-21F); RGC-CRF (C4008-23W); Strategic Seed Funding Collaboration Research Scheme CUHK (3133344); Strategic Impact Enhancement Fund CUHK (3135509); Impact case for RAE CUHK (3134277).

Infiltration of CD8+ cytotoxic T-cells and expression of PD-1 and PD-L1 in ovarian clear cell carcinoma

Ovarian clear cell carcinoma (OCCC) is resistant to chemotherapy, with limited treatment options for advanced and recurrent disease. The prevalence of OCCC differs by region. Assessing the expression of programmed cell death ligand 1 (PD-L1), PD-1, and CD8+T cell infiltration in OCCC is crucial, as their correlation with patient survival may provide valuable prognostic insights. We collected data from 36 samples from 18 OCCC patients, including 18 pairs of tumors and adjacent nonneoplastic samples. The optimized multiplex immunofluorescence technique was used to stain paraffin sections for immune factors related to the immune microenvironment of OCCC and clinical prognosis. The expression of PDL1 and PD1 in the tumor cells and tumor stromal cells was not significantly correlated with prognosis. Professional quantitative pathological analysis software was used to count the CD8+ cytotoxic T-cells in tumor regions and adjacent nonneoplastic regions in postoperative specimens. There were more CD8+ cytotoxic T-cells in the adjacent nonneoplastic areas than in the tumor tissue samples (p < 0.001). Further analysis revealed that a difference in cell density between CD8+ non-tumor-infiltrating lymphocytes (NTILs) and CD8+ tumor-infiltrating lymphocytes (TILs) exceeding 70 cells/mm2 was associated with poorer progression-free survival (PFS) (p = 0.042). In adjacent nonneoplastic regions, worse PFS was significantly observed in patients with high CD8+ T-cell expression in both total and stromal cells than those with low expression (p = 0.012 vs p = 0.007). The presence of CD8+ T-cells had significant potential for predicting the prognosis of patients with OCCC, which lays a foundation for the development of biomarkers for immune checkpoint blockade treatment response in OCCC patients.

Mapping naturally presented T cell antigens in medulloblastoma based on integrative multi-omics

Medulloblastoma is the most frequent malignant primary brain tumor in children. Despite recent advances in integrated genomics, the prognosis in children with high-risk medulloblastoma remains devastating, and new tumor-specific therapeutic approaches are needed. Here, we present an atlas of naturally presented T cell antigens in medulloblastoma. We map the human leukocyte antigen (HLA)-presented peptidomes of 28 tumors and perform comparative immunopeptidome profiling against an in-house benign database. Medulloblastoma is shown to be a rich source of tumor-associated antigens, naturally presented on HLA class I and II molecules. Remarkably, most tumor-associated peptides and proteins are subgroup-specific, whereas shared presentation among all subgroups of medulloblastoma (WNT, SHH, Group 3 and Group 4) is rare. Functional testing of top-ranking novel candidate antigens demonstrates the induction of peptide-specific T cell responses, supporting their potential for T cell immunotherapy. This study is an in-depth mapping of naturally presented T cell antigens in medulloblastoma. Integration of immunopeptidomics, transcriptomics, and epigenetic data leads to the identification of a large set of actionable targets that can be further used for the translation into the clinical setting by facilitating the informed design of immunotherapeutic approaches to children with medulloblastoma.

A deep learning framework for in silico screening of anticancer drugs at the single-cell level

Tumor heterogeneity plays a pivotal role in tumor progression and resistance to clinical treatment. Single-cell RNA sequencing (scRNA-seq) enables us to explore heterogeneity within a cell population and identify rare cell types, thereby improving our design of targeted therapeutic strategies. Here, we use a pan-cancer and pan-tissue single-cell transcriptional landscape to reveal heterogeneous expression patterns within malignant cells, precancerous cells, as well as cancer-associated stromal and endothelial cells. We introduce a deep learning framework named Shennong for in silico screening of anticancer drugs for targeting each of the landscape cell clusters. Utilizing Shennong, we could predict individual cell responses to pharmacologic compounds, evaluate drug candidates' tissue damaging effects, and investigate their corresponding action mechanisms. Prioritized compounds in Shennong's prediction results include FDA-approved drugs currently undergoing clinical trials for new indications, as well as drug candidates reporting anti-tumor activity. Furthermore, the tissue damaging effect prediction aligns with documented injuries and terminated discovery events. This robust and explainable framework has the potential to accelerate the drug discovery process and enhance the accuracy and efficiency of drug screening.

Molecular diagnosis of nasopharyngeal carcinoma: Past and future

Nasopharyngeal carcinoma (NPC) is a malignant tumor originated from the nasopharynx epithelial cells and has been linked with Epstein-Barr virus (EBV) infection, dietary habits, environmental and genetic factors. It is a common malignancy in Southeast Asia, especially with gender preference among men. Due to its non-specific symptoms, NPC is often diagnosed at a late stage. Thus, the molecular diagnosis of NPC plays a crucial role in early detection, treatment selection, disease monitoring, and prognosis prediction. This review aims to provide a summary of the current state and the latest emerging molecular diagnostic techniques for NPC, including EBV-related biomarkers, gene mutations, liquid biopsy, and DNA methylation. Challenges and potential future directions of NPC molecular diagnosis will be discussed.

uniLIVER: a human liver cell atlas for data-driven cellular state mapping

The liver performs several vital functions such as metabolism, toxin removal, and glucose storage through the coordination of various cell types. With the recent breakthrough of the single-cell/single-nucleus RNA-seq (sc/snRNA-seq) techniques, there is a great opportunity to establish a reference cell map of the liver at single-cell resolution with transcriptome-wise features. In this study, we build a unified liver cell atlas uniLIVER (http://lifeome.net/database/uniliver) by integrative analysis of a large-scale sc/snRNA-seq data collection of normal human liver with 331,125 cells and 79 samples from 6 datasets. Moreover, we introduce LiverCT, a novel machine learning based method for mapping any query dataset to the liver reference map by introducing the definition of "variant" cellular states analogy to the sequence variants in genomic analysis. Applying LiverCT on liver cancer datasets, we find that the "deviated" states of T cells are highly correlated with the stress pathway activities in hepatocellular carcinoma, and the enrichments of tumor cells with the hepatocyte-cholangiocyte "intermediate" states significantly indicate poor prognosis. Besides, we find that the tumor cells of different patients have different zonation tendencies and this zonation tendency is also significantly associated with the prognosis. This reference atlas mapping framework can also be extended to any other tissues.

Deep learning model targeting cancer surrounding tissues for accurate cancer diagnosis based on histopathological images

Accurate and fast histological diagnosis of cancers is crucial for successful treatment. The deep learning-based approaches have assisted pathologists in efficient cancer diagnosis. The remodeled microenvironment and field cancerization may enable the cancer-specific features in the image of non-cancer regions surrounding cancer, which may provide additional information not available in the cancer region to improve cancer diagnosis. Here, we proposed a deep learning framework with fine-tuning target proportion towards cancer surrounding tissues in histological images for gastric cancer diagnosis. Through employing six deep learning-based models targeting region-of-interest (ROI) with different proportions of no-cancer and cancer regions, we uncovered the diagnostic value of non-cancer ROI, and the model performance for cancer diagnosis depended on the proportion. Then, we constructed a model based on MobileNetV2 with the optimized weights targeting non-cancer and cancer ROI to diagnose gastric cancer (DeepNCCNet). In the external validation, the optimized DeepNCCNet demonstrated excellent generalization abilities with an accuracy of 93.96%. In conclusion, we discovered a non-cancer ROI weight-dependent model performance, indicating the diagnostic value of non-cancer regions with potential remodeled microenvironment and field cancerization, which provides a promising image resource for cancer diagnosis. The DeepNCCNet could be readily applied to clinical diagnosis for gastric cancer, which is useful for some clinical settings such as the absence or minimum amount of tumor tissues in the insufficient biopsy.

Fecal Microbiota Strongly Correlates with Tissue Microbiota Composition in Colorectal Cancer but Not in Non-Small Cell Lung Cancer

Microbiota could be of interest in the diagnosis of colorectal and non-small cell lung cancer (CRC and NSCLC). However, how the microbial components of tissues and feces reflect each other remains unknown. In this work, our main objective is to discover the degree of correlation between the composition of the tissue microbiota and that of the feces of patients affected by CRC and NSCLC. Specifically, we investigated tumor and non-tumor tissues from 38 recruited patients with CRC and 19 with NSCLC. DNA from samples was submitted for 16S rDNA metagenomic sequencing, followed by data analysis through the QIIME2 pipeline and further statistical processing with STATA IC16. Tumor and non-tumor tissue selected genera were highly correlated in both CRC and NSCLC (100% and 81.25%). Following this, we established tissue-feces correlations, using selected genera from a LEfSe analysis previously published. In CRC, we found a strong correlation between the taxa detected in feces and those from colorectal tissues. However, our data do not demonstrate this correlation in NSCLC. In conclusion, our findings strongly reinforce the utility of fecal microbiota as a non-invasive biomarker for CRC diagnosis, while highlighting critical distinctions for NSCLC. Furthermore, our data demonstrate that the microbiota components of tumor and non-tumor tissues are similar, with only minor differences being detected.

Investigation of Exome-Wide Tumor Heterogeneity on Colorectal Tissue-Based Single Cells

The progression of colorectal cancer is strongly influenced by environmental and genetic conditions. One of the key factors is tumor heterogeneity which is extensively studied by cfDNA and bulk sequencing methods; however, we lack knowledge regarding its effects at the single-cell level. Motivated by this, we aimed to employ an end-to-end single-cell sequencing workflow from tissue-derived sample isolation to exome sequencing. Our main goal was to investigate the heterogeneity patterns by laser microdissecting samples from different locations of a tissue slide. Moreover, by studying healthy colon control, tumor-associated normal, and colorectal cancer tissues, we explored tissue-specific heterogeneity motifs. For completeness, we also compared the performance of the whole-exome bulk, cfDNA, and single-cell sequencing methods based on variation at the level of a single nucleotide.

Comprehensive multi-omics analysis identifies NUSAP1 as a potential prognostic and immunotherapeutic marker for lung adenocarcinoma

While NUSAP1's association with various tumors is established, its predictive value for prognosis and immunotherapy in lung adenocarcinoma (LUAD) remains unconfirmed. We analyzed Nucleolar Spindle-Associated Protein 1 (NUSAP1) gene expression in TCGA and GTEx datasets and validated it in clinicopathological tissues using qRT-PCR and immunohistochemistry. Additionally, we investigated NUSAP1's relationship with patient prognosis across TCGA and five GEO cohorts. The IMvigor210 cohort was utilized to explore NUSAP1's association with immunotherapy efficacy. Furthermore, single-cell RNA-sequencing data was used to examine the correlation between NUSAP1 and immune cell infiltration. Finally, we analyzed the relationship between NUSAP1 and m6A methylation. NUSAP1 expression was significantly elevated in tumor tissues, correlating with poorer prognosis in LUAD patients. It exhibited a significant correlation with immune cell infiltration in the tumor microenvironment, predominantly expressed in Tprolif cells. LUAD patients with heightened NUSAP1 expression may derive greater benefit from anti-PD-L1 treatment. Additionally, NUSAP1 was tightly linked with m6A methylation. Enrichment analysis revealed its association with key biological functions, including lipid metabolism and cell cycle regulation. Our comprehensive analysis underscores NUSAP1's potential as a prognostic and immunotherapeutic biomarker for LUAD, warranting further investigation.

Loss of Kmt2c or Kmt2d primes urothelium for tumorigenesis and redistributes KMT2A-menin to bivalent promoters

Members of the KMT2C/D-KDM6A complex are recurrently mutated in urothelial carcinoma and in histologically normal urothelium. Here, using genetically engineered mouse models, we demonstrate that Kmt2c/d knockout in the urothelium led to impaired differentiation, augmented responses to growth and inflammatory stimuli and sensitization to oncogenic transformation by carcinogen and oncogenes. Mechanistically, KMT2D localized to active enhancers and CpG-poor promoters that preferentially regulate the urothelial lineage program and Kmt2c/d knockout led to diminished H3K4me1, H3K27ac and nascent RNA transcription at these sites, which leads to impaired differentiation. Kmt2c/d knockout further led to KMT2A-menin redistribution from KMT2D localized enhancers to CpG-high and bivalent promoters, resulting in derepression of signal-induced immediate early genes. Therapeutically, Kmt2c/d knockout upregulated epidermal growth factor receptor signaling and conferred vulnerability to epidermal growth factor receptor inhibitors. Together, our data posit that functional loss of Kmt2c/d licenses a molecular 'field effect' priming histologically normal urothelium for oncogenic transformation and presents therapeutic vulnerabilities.

Identification of a distinctive immunogenomic gene signature in stage-matched colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Despite advances in diagnosis and treatment, including surgery, chemotherapy, and immunotherapy, accurate clinical markers are still lacking. The development of prognostic and predictive indicators, particularly in the context of personalized medicine, could significantly improve CRC patient management.

METHOD

In this retrospective study, we used FFPE blocks of tissue samples from CRC patients at Augusta University (AU) to quantify a custom 15-gene panel. To differentiate the tumor and adjacent normal regions (NAT), H&E staining was utilized. For the quantification of transcripts, we used the NanoString nCounter platform. Kaplan-Meier and Log-rank tests were used to perform survival analyses. Several independent datasets were explored to validate the gene signature. Orthogonal analyses included single-cell profiling, differential gene expression, immune cell deconvolution, neoantigen prediction, and biological pathway assessment.

RESULTS

A 3-gene signature (GTF3A, PKM, and VEGFA) was found to be associated with overall survival in the AU cohort (HR = 2.26, 95% CI 1.05-4.84, p = 0.02, 93 patients), TCGA cohort (HR = 1.57, 95% CI 1.05-2.35, p < 0.02, 435 patients) and four other GEO datasets. Independent single-cell analysis identified relatively higher expression of the 3-gene signature in the tumor region. Differential analysis revealed dysregulated tissue inflammation, immune dysfunction, and neoantigen load of cell cycle processes among high-risk patients compared to low-risk patients.

CONCLUSION

We developed a 3-gene signature with the potential for prognostic and predictive clinical assessment of CRC patients. This gene-based stratification offers a cost-effective approach to personalized cancer management. Further research using similar methods could identify therapy-specific gene signatures to strengthen the development of personalized medicine for CRC patients.

Nuclear translocation of plasma membrane protein ADCY7 potentiates T cell-mediated antitumour immunity in HCC

BACKGROUND

The potency of T cell-mediated responses is a determinant of immunotherapy effectiveness in treating malignancies; however, the clinical efficacy of T-cell therapies has been limited in hepatocellular carcinoma (HCC) owing to the extensive immunosuppressive microenvironment.

OBJECTIVE

Here, we aimed to investigate the key genes contributing to immune escape in HCC and raise a new therapeutic strategy for remoulding the HCC microenvironment.

DESIGN

The genome-wide in vivo clustered regularly interspaced short palindromic repeats (CRISPR) screen library was conducted to identify the key genes associated with immune tolerance. Single-cell RNA-seq (scRNA-seq), flow cytometry, HCC mouse models, chromatin immunoprecipitation and coimmunoprecipitation were used to explore the function and mechanism of adenylate cyclase 7 (ADCY7) in HCC immune surveillance.

RESULTS

Here, a genome-wide in vivo CRISPR screen identified a novel immune modulator-ADCY7. The transmembrane protein ADCY7 undergoes subcellular translocation via caveolae-mediated endocytosis and then translocates to the nucleus with the help of leucine-rich repeat-containing protein 59 (LRRC59) and karyopherin subunit beta 1 (KPNB1). In the nucleus, it functions as a transcription cofactor of CCAAT/enhancer binding protein alpha (CEBPA) to induce CCL5 transcription, thereby increasing CD8+ T cell infiltration to restrain HCC progression. Furthermore, ADCY7 can be secreted as exosomes and enter neighbouring tumour cells to promote CCL5 induction. Exosomes with high ADCY7 levels promote intratumoural infiltration of CD8+ T cells and suppress HCC tumour growth.

CONCLUSION

We delineate the unconventional function and subcellular location of ADCY7, highlighting its pivotal role in T cell-mediated immunity in HCC and its potential as a promising treatment target.

Genomes and epigenomes of matched normal and tumor breast tissue reveal diverse evolutionary trajectories and tumor-host interactions

Normal tissues adjacent to the tumor (NATs) may harbor early breast carcinogenesis events driven by field cancerization. Although previous studies have characterized copy-number (CN) and transcriptomic alterations, the evolutionary history of NATs in breast cancer (BC) remains poorly characterized. Utilizing whole-genome sequencing (WGS), methylation profiling, and RNA sequencing (RNA-seq), we analyzed paired germline, NATs, and tumor samples from 43 individuals with BC in Hong Kong (HK). We found that single-nucleotide variants (SNVs) were common in NATs, with one-third of NAT samples exhibiting SNVs in driver genes, many of which were present in paired tumor samples. The most frequently mutated genes in both tumor and NAT samples were PIK3CA, TP53, GATA3, and AKT1. In contrast, large-scale aberrations such as somatic CN alterations (SCNAs) and structural variants (SVs) were rarely detected in NAT samples. We generated phylogenetic trees to investigate the evolutionary history of paired NAT and tumor samples. They could be categorized into tumor only, shared, and multiple-tree groups, the last of which is concordant with non-genetic field cancerization. These groups exhibited distinct genomic and epigenomic characteristics in both NAT and tumor samples. Specifically, NAT samples in the shared-tree group showed higher number of mutations, while NAT samples belonging to the multiple-tree group showed a less inflammatory tumor microenvironment (TME), characterized by a higher proportion of regulatory T cells (Tregs) and lower presence of CD14 cell populations. In summary, our findings highlight the diverse evolutionary history in BC NAT/tumor pairs and the impact of field cancerization and TME in shaping the genomic evolutionary history of tumors.

Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study

Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, and a notably low five-year survival rate, underscoring the critical need for early detection methods and more effective therapeutic approaches. This research rigorously investigates the molecular mechanisms underlying PDAC, with a focus on the identification of pivotal genes and pathways that may hold therapeutic relevance and prognostic value. Through the construction of a protein-protein interaction (PPI) network and the examination of differentially expressed genes (DEGs), the study uncovers key hub genes such as CDK1, KIF11, and BUB1, demonstrating their substantial role in the pathogenesis of PDAC. Notably, the dysregulation of these genes is consistent across a spectrum of cancers, positing them as potential targets for wide-ranging cancer therapeutics. This study also brings to the fore significant genes encoding intrinsically disordered proteins, in particular GPRC5A and KRT7, unveiling promising new pathways for therapeutic intervention. Advanced machine learning techniques were harnessed to classify PDAC patients with high accuracy, utilizing the key genetic markers as a dataset. The Support Vector Machine (SVM) model leveraged the hub genes to achieve a sensitivity of 91 % and a specificity of 85 %, while the RandomForest model notched a sensitivity of 91 % and specificity of 92.5 %. Crucially, when the identified genes were cross-referenced with TCGA-PAAD clinical datasets, a tangible correlation with patient survival rates was discovered, reinforcing the potential of these genes as prognostic biomarkers and their viability as targets for therapeutic intervention. This study's findings serve as a potent testament to the value of molecular analysis in enhancing the understanding of PDAC and in advancing the pursuit for more effective diagnostic and treatment strategies.

Proteogenomic Landscape of Breast Ductal Carcinoma Reveals Tumor Progression Characteristics and Therapeutic Targets

Multi-omics studies of breast ductal carcinoma (BRDC) have advanced the understanding of the disease's biology and accelerated targeted therapies. However, the temporal order of a series of biological events in the progression of BRDC is still poorly understood. A comprehensive proteogenomic analysis of 224 samples from 168 patients with malignant and benign breast diseases is carried out. Proteogenomic analysis reveals the characteristics of linear multi-step progression of BRDC, such as tumor protein P53 (TP53) mutation-associated estrogen receptor 1 (ESR1) overexpression is involved in the transition from ductal hyperplasia (DH) to ductal carcinoma in situ (DCIS). 6q21 amplification-associated nuclear receptor subfamily 3 group C member 1 (NR3C1) overexpression helps DCIS_Pure (pure DCIS, no histologic evidence of invasion) cells avoid immune destruction. The T-cell lymphoma invasion and metastasis 1, androgen receptor, and aldo-keto reductase family 1 member C1 (TIAM1-AR-AKR1C1) axis promotes cell invasion and migration in DCIS_adjIDC (DCIS regions of invasive cancers). In addition, AKR1C1 is identified as a potential therapeutic target and demonstrated the inhibitory effect of aspirin and dydrogesterone as its inhibitors on tumor cells. The integrative multi-omics analysis helps to understand the progression of BRDC and provides an opportunity to treat BRDC in different stages.

High expression of BBOX1 in paracancerous tissue is associated with poor prognosis in hepatocellular carcinoma patients

The molecular profile of paracancerous tissue has been reported to be prognostic for recurrence in patients with different cancers. This study investigated the clinical significance of the protein expression of gamma-butyrobetaine hydroxylase 1 (BBOX1) in tumor and paracancerous tissues of hepatocellular carcinoma (HCC) patients. This study assessed the role of BBOX1 mRNA in tumor and paracancerous tissues in HCC via bioinformatics analysis. The protein levels of BBOX1 in paired tumor and paracancerous tissues from 83 HCC patients were determined by immunohistochemistry. The associations among BBOX1 protein levels, clinicopathological characteristics and the survival probability of HCC patients were also analyzed. The results revealed that BBOX1 mRNA expression was significantly lower in HCC tissues than in noncancerous tissues. HCC patients with low BBOX1 mRNA expression had a significantly poorer overall survival than those with high BBOX1 expression did. Immunohistochemical analysis of BBOX1 protein expression further confirmed that its levels were markedly lower in HCC tissues than in paracancerous tissues. High BBOX1 expression in paracancerous tissues correlated with poor overall survival and disease-free survival in HCC patients. These findings suggest that the paracancerous BBOX1 expression might be a credible indicator for overall survival or disease-free survival in HCC patients.

Volumetric body composition analysis of the Cancer Genome Atlas reveals novel body composition traits and molecular markers Associated with Renal Carcinoma outcomes

Clinically, the body mass index remains the most frequently used metric of overall obesity, although it is flawed by its inability to account for different adipose (i.e., visceral, subcutaneous, and inter/intramuscular) compartments, as well as muscle mass. Numerous prior studies have demonstrated linkages between specific adipose or muscle compartments to outcomes of multiple diseases. Although there are no universally accepted standards for body composition measurement, many studies use a single slice at the L3 vertebral level. In this study, we use computed tomography (CT) studies from patients in The Cancer Genome Atlas (TCGA) to compare current L3-based techniques with volumetric techniques, demonstrating potential limitations with level-based approaches for assessing outcomes. In addition, we identify gene expression signatures in normal kidney that correlate with fat and muscle body composition traits that can be used to predict sex-specific outcomes in renal cell carcinoma.

High-confidence calling of normal epithelial cells allows identification of a novel stem-like cell state in the colorectal cancer microenvironment

Single-cell analyses can be confounded by assigning unrelated groups of cells to common developmental trajectories. For instance, cancer cells and admixed normal epithelial cells could adopt similar cell states thus complicating analyses of their developmental potential. Here, we develop and benchmark CCISM (for Cancer Cell Identification using Somatic Mutations) to exploit genomic single nucleotide variants for the disambiguation of cancer cells from genomically normal non-cancer cells in single-cell data. We find that our method and others based on gene expression or allelic imbalances identify overlapping sets of colorectal cancer versus normal colon epithelial cells, depending on molecular characteristics of individual cancers. Further, we define consensus cell identities of normal and cancer epithelial cells with higher transcriptome cluster homogeneity than those derived using existing tools. Using the consensus identities, we identify significant shifts of cell state distributions in genomically normal epithelial cells developing in the cancer microenvironment, with immature states increased at the expense of terminal differentiation throughout the colon, and a novel stem-like cell state arising in the left colon. Trajectory analyses show that the new cell state extends the pseudo-time range of normal colon stem-like cells in a cancer context. We identify cancer-associated fibroblasts as sources of WNT and BMP ligands potentially contributing to increased plasticity of stem cells in the cancer microenvironment. Our analyses advocate careful interpretation of cell heterogeneity and plasticity in the cancer context and the consideration of genomic information in addition to gene expression data when possible.

Overexpression of human DNA polymerase theta is a biomarker of aggressive and DNA repair-deficient papillary thyroid cancers

BACKGROUND

DNA polymerase theta (POLQ) is an enzyme that repairs double-strand DNA breaks. POLQ is overexpressed in several cancer types, and increased expression is associated with a poor prognosis. Ablating POLQ function in vitro increases drug sensitivity to agents that cause double-strand DNA breaks, including chemotherapies and ionizing radiation. POLQ's role in thyroid cancer remains poorly understood.

METHODS

Expression of POLQ and other genes of interest were analyzed in 513 papillary thyroid cancers (505 primary tumors and 8 metastatic lesions) and 59 normal thyroid samples available in the Cancer Genome Atlas. The Cancer Genome Atlas RNA and DNA sequencing data were queried with the Xena platform. The Recombination Proficiency Score was calculated to assess DNA repair efficiency. Other signaling events associated with thyroid tumorigenesis and clinical outcomes were analyzed. Univariate and multivariate analyses were performed. Treatment with the POLQ inhibitors ART558 and Novobiocin tested the effect of POLQ inhibition on in vitro thyroid cancer growth.

RESULTS

POLQ expression was increased in papillary thyroid cancers compared to normal thyroid tissue (P < .05). POLQ expression levels were inversely correlated with Recombination Proficiency Score levels (P < .05). POLQ expression was highest in tall cell papillary thyroid cancers and in metastases. Higher POLQ expression was also associated with dedifferentiation, BRAF signaling, and shorter progression-free intervals (P < .05). Treatment with POLQ inhibitors decreased in vitro thyroid cancer growth (P < .05).

CONCLUSION

These findings suggest that increased POLQ expression could serve as a valuable clinical marker and a potential therapeutic target in the treatment of thyroid cancer.

Differentially Expressed Somatostatin (SST) and Its Receptors (SST1-5) in Sporadic Colorectal Cancer and Normal Colorectal Mucosa

BACKGROUND/OBJECTIVES

Colorectal cancer (CRC) is one of the most common human malignancies worldwide. The somatotropin-releasing inhibitory factor/somatostatin (SRIF/SST) acts through activation of five membrane receptors (SSTRs, SST1-5). The diagnostic and prognostic role of these peptides in sporadic CRC remains unclear. This study aimed to determine the role of tissue expression of SST and all SSTRs in the pathogenesis, diagnosis, and prognosis of sporadic CRC.

METHODS

The expression of SST and all SSTRs was assessed in the tissues of CRC patients, control colorectal mucosa and lymph node metastasis from the same patients using real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC).

RESULTS

Decreased SST (mRNA and peptide) and higher SST2 and SST5 (mRNA and peptide) expression in CRC vs. control was noted. A negative correlation between SST mRNA expression and patient's age in CRC and control groups were observed. IHC study confirmed the coexpression of SSTRs in all tissue groups and significant dependence on the cellular localization. Immunoexpression of SST2 and SST3 showed the most correlations with clinicopathological data in CRC patients. Interestingly, only control tissue showed differences in SST1-5 expression depending on the colon segment.

CONCLUSIONS

Reduced SST expression in CRC indicates a weakening in its antitumor effect in this cancer in vivo. Overexpression of SST2 and SST5 in CRC suggests that these receptors play an important role in the pathogenesis of this cancer. Analysis of SST1-5 tissue expression allows for differentiation between the mucinous and nonmucinous CRC subtypes. The coexpression of all SST1-5 and overexpression of not only SST2 and SST5 in CRC may have applications for future therapy based on the SRIF system in sporadic CRC.

Exploring the Chemopreventive Effect of Medication on Gene Expression Linked to Colorectal Cancer: An Observational and Mendelian Randomization Analysis in Healthy Colon Mucosa

Gene expression appears altered in apparently normal tissue surrounding tumor tissue. The observed biological alterations in the tumor microenvironment play a crucial role in cancer development and are named the cancer field effect (FE). A robust set of overexpressed FE genes in tissue surrounding colorectal cancer (CRC) tumor were identified in previous studies. Our study aimed to investigate the influence of common medication intake and modifiable risk factors on FE gene expression using a colonic mucosa sample dataset of healthy individuals (BarcUVa-Seq). We applied expression enrichment analysis of the FE genes for each studied medication and factor. Both observational and instrumental (Mendelian randomization) analysis were conducted, and the results were validated using independent datasets. The findings from the observational and instrumental analyses consistently showed that medication intake, especially metformin, considerably downregulated the FE genes. Chemopreventive effects were also noted for antihypertensive drugs targeting the renin-angiotensin system. Conversely, benzodiazepines usage might upregulate FE genes, thus fostering a tumor-promoting microenvironment. In contrast, the findings from the observational and instrumental analyses on modifiable risk factors showed some discrepancies. The instrumental results indicated that obesity and smoking might promote a tumor-favorable microenvironment. These findings offer insights into the biological mechanisms through which risk factors might influence CRC development and highlight the potential chemopreventive roles of metformin and antihypertensive drugs in CRC risk.

ELiAH: the atlas of E3 ligases in human tissues for targeted protein degradation with reduced off-target effect

The development of therapeutic agents has mainly focused on designing small molecules to modulate target proteins or genes which are conventionally druggable. Therefore, targeted protein degradation (TPD) for undruggable cases has emerged as promising pharmaceutical approach. TPD, often referred PROTACs (PROteolysis TArgeting Chimeras), uses a linker to degrade target proteins by hijacking the ubiquitination system. Therefore, unravel the relationship including reversal and co-expression between E3 ligands and other possible target genes in various human tissues is essential to mitigate off-target effects of TPD. Here, we developed the atlas of E3 ligases in human tissues (ELiAH), to prioritize E3 ligase-target gene pairs for TPD. Leveraging over 2900 of RNA-seq profiles consisting of 11 human tissues from the GTEx (genotype-tissue expression) consortium, users of ELiAH can identify tissue-specific genes and E3 ligases (FDR P-value of Mann-Whitney test < .05). ELiAH unravels 933 830 relationships consisting of 614 E3 ligases and 20 924 of expressed genes considering degree of tissue specificity, which are indispensable for ubiquitination based TPD development. In addition, docking properties of those relationships are also modeled using RosettaDock. Therefore, ELiAH presents comprehensive repertoire of E3 ligases for ubiquitination-based TPD drug development avoiding off-target effects. Database URL: https://eliahdb.org.

Unraveling bidirectional evolution of unstable mitochondrial DNA mutations in hepatocellular carcinoma at single-cell resolution

BACKGROUND AND AIMS

Somatic mutations in mitochondrial DNA (mtDNA) are abundant in HCC and directly affect metabolic homeostasis and tumor progression. The mixed population of mutant and wild-type mtDNA alleles within a cell, termed heteroplasmy, can vary from cell-to-cell and orchestrate tumorigenesis. However, the systematic evolutionary dynamics of somatic mtDNA mutations in HCC tissues remain to be delineated at single-cell resolution.

APPROACH AND RESULTS

We established the single-cell capture-based mtDNA sequencing approach for accurately detecting somatic mtDNA mutations at single-cell resolution. Based on single-cell capture-based mtDNA sequencing, the single-cell somatic mtDNA mutational landscape, intratumor heterogeneity (ITH), and spatiotemporal clonal evolution were systematically investigated in 1641 single cells from 11 patients with HCC and 528 single cells from 2 patient-derived xenografts mouse models. Our data revealed the presence of 2 distinct categories of mtDNA mutation at single-cell resolution, including stable mutations exhibiting similar heteroplasmy levels and unstable mutations exhibiting remarkable cell-to-cell variability of heteroplasmy levels. Furthermore, the proportion of unstable mtDNA mutations was positively associated with the ITH of patients with HCC, with high ITH reflecting the proliferative and aggressive clinicopathological features of HCC cells. In addition, reconstruction of the evolutionary history classified HCC evolution patterns as linear or branched. Notably, spatiotemporal lineage tracing in patient-derived xenograft mouse models and multifocal lesions revealed bidirectional evolution of unstable mtDNA mutations during HCC progression.

CONCLUSIONS

Our study unravels the landscape of single-cell somatic mtDNA mutations in HCC tissues and reveals the bidirectional evolution of unstable mtDNA mutations, with potential implications for HCC stratification and therapeutic intervention.

Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma

BACKGROUND

Lung cancer is the most common cause of cancer-related death worldwide. The most prevalent histological subtype of lung cancer is lung adenocarcinoma (LUAD), with incidence rising each year. Treating LUAD remains a significant issue due to a lack of early diagnosis and poor therapy outcomes. YKT6 is a member of the SNARE protein family, whose clinical value and biological function in LUAD has yet to be established.

METHODS

TCGA, HPA and UALCAN were used to analyze YKT6 mRNA and protein levels, the correlation between YKT6 expression and clinicopathological features and prognosis. YKT6 mRNA and protein expression were verified by qRT-PCR, immunohistochemistry (IHC) and tissue microarrays (TMA). Additionally, lung cancer cell lines were chosen for YKT6 silencing to explore the effects on cell proliferation and migration. The cBioPortal was used to select YKT6-related genes. Protein-protein interaction (PPI) network was created based on STRING database and hub genes were screened, with their expression levels and prognosis values in LUAD analyzed accordingly. YKT6-related genes were enriched by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses.

RESULTS

In LUAD, YKT6 was distinctly highly expressed with relation to clinical features of staging, smoking, lymph node metastasis, and TP53 mutation. Elevated YKT6 expression was linked to adverse prognosis, serving as an independent unfavorable prognostic factor. Moreover, YKT6 presented high diagnostic value in LUAD patients (AUC = 0.856). Experimental validation indicated that freshly collected LUAD tissues showed significantly high mRNA expression of YKT6. IHC and TMA verified increased YKT6 protein level in LUAD. Knockdown of YKT6 inhibited cell proliferation and promoted apoptosis, with mitigated capability of migration and invasion. The top ten hub genes screened by PPI network were highly expressed in LUAD, and significantly associated with poor prognosis. GO and KEGG analyses showed that YKT6-related genes were mainly involved in cell cycle.

CONCLUSION

Elevated YKT6 expression is related to poor prognosis of LUAD patients. YKT6 can serve as a novel biomarker for LUAD diagnosis and prognosis. Cell proliferation, migration and invasion was impaired with increased apoptosis upon YKT6 silencing in lung cancer cells. In summary, this study comprehensively uncovered that YKT6 could be identified as a potential prognostic and diagnostic biomarker in LUAD.

Peritumoral tissue (PTT): increasing need for naming convention

Various terms are used to describe non-malignant tissue located in the proximity of a tumor, belonging to the organ from which the tumor originated. Traditionally, these tissues, sometimes called "normal adjacent tissue" have been used as controls in cancer studies, and were considered representative of morphologically healthy, non-cancerous tissue. However, with the advancement of OMIC technologies, such tissues are increasingly recognized to be distinct from both tumor and healthy tissues. Furthermore, properties, characteristics, and role of these tissues in cancer formation and progression is increasingly studied. In order to make future research in this area more harmonized and more accessible, as well as to counter the widespread perception of normalcy, we are advocating the need for standardized naming convention. For this purpose, we propose the use of neutral and comprehensive term "Peritumoral Tissue" along with the acronym "PTT". While significant amount of data on these tissues are publicly available, reuse of such data remains limited due to a lack of information on sample collection procedures. In order to facilitate future reuse of the data, we suggest a list of features that should be documented during sample collection procedures. These recommendations can aid the definition of Standard Operating Procedures.

The potential of enteroids derived from children and adults to study age-dependent differences in intestinal CYP3A4/5 metabolism

Drug metabolism in the intestinal wall affects bioavailability of orally administered drugs and is influenced by age. Hence, it is important to fully understand the drug metabolizing capacity of the gut to predict systemic exposure. The aim of this study was to investigate the potential of enteroids as a tool to study CYP3A4/5 -mediated metabolism in both children and adults. Bioconversion of midazolam, a CYP3A4/5 model substrate, was studied using enteroid monolayers as well as tissue explants in the Ussing chamber, both derived from pediatric [median (range age): 54 weeks (2 days - 13 years), n = 21] and adult (n = 5) tissue. Caco-2 cellular monolayers were employed as controls. In addition, mRNA expression of CYP3A4 was determined in enteroid monolayers (n = 11), tissue (n = 23) and Caco-2 using RT-qPCR. Midazolam metabolism was successfully detected in all enteroid monolayers, as well as in all tissue explants studied in the Ussing chamber, whereas Caco-2 showed no significant metabolite formation. The extracted fraction of midazolam was similar between enteroid monolayers and tissue. The fraction of midazolam extracted increased with age in enteroid monolayers derived from 0 to 70 week old donors. No statistically significant correlation was observed in tissue likely due to high variability observed and the smaller donor numbers included in the study. At the level of gene expression, CYP3A4 increased with age in tissues (n = 32), while this was not reflected in enteroid monolayers (n = 16). Notably, asymmetric metabolite formation was observed in enteroids and tissue, with higher metabolite formation on the luminal side of the barrier. In summary, we demonstrated that enteroids can be used to measure CYP3A4/5 midazolam metabolism, which we show is similar as observed in fresh isolated tissue. This was the case both in children and adults, indicating the potential of enteroids to predict intestinal metabolism. This study provides promising data to further develop enteroids to study drug metabolism in vitro and potentially predict oral absorption for special populations as an alternative to using fresh tissue.

Upregulation of Apoptosis Related Genes in Clinically Normal Tongue Contralateral to Squamous Cell Carcinoma of the Oral Tongue, an Effort to Maintain Tissue Homeostasis

PURPOSE

The field cancerization concept indicates the presence of pre-cancerous changes in clinically normal tissue surrounding the tumor. In squamous cell carcinoma of the oral tongue (SCCOT) which is infrequently linked to human papillomavirus infection, we have previously reported that clinically normal tongue contralateral to tumor (NTCT) is molecularly abnormal. Here, combining our transcriptomic and genomic data, we aimed to investigate the contribution of molecular changes in NTCT to cancer development.

METHODS

Microarray gene expression data of 14 healthy controls, 23 NTCT and 29 SCCOT samples were investigated to characterize transcriptional profiles in NTCT. Whole exome sequencing and RNA-sequencing data of paired NTCT and tumor samples from 15 SCCOT patients were used to study correlation between copy number variation and differential gene expression.

RESULTS

Using supervised multivariate partial least squares discriminant analysis, a total of 61 mRNAs that distinguish NTCT from healthy tongue were selected. Functional enrichment analysis of the 22 upregulated genes showed increased "positive regulation of nitrogen compound metabolic process" in NTCT. All 12 genes involved in this process have roles in apoptosis (anti- and/or pro-apoptotic). Compared to healthy controls, Zinc Finger Protein 395 (ZNF395), a pro-apoptotic tumor suppressor located on chromosome 8p, was the only gene showing increased mRNA level in NTCT whereas decreased in SCCOT. Given the frequent loss of chromosome 8p in SCCOT, the impact of ZNF395 copy number variation on gene expression was further examined, revealing a positive correlation between copy number and mRNA level (correlation coefficient = 0.572, p < 0.001).

CONCLUSION

NTCT is susceptible to malignant transformation, where tissue homeostasis is maintained at least partly through regulation of apoptosis. Loss of the pro-apoptotic gene ZNF395 could thus initiate cancer development.

The association between infectious agents and breast cancer: a review of the epidemiologic evidence

PURPOSE

Several viruses have been casually linked to human cancers, including cervical, nasopharyngeal, liver, sarcoma, and Merkel cell carcinomas. However, the etiologic contribution of viral infections to breast cancer, the number one incident cancer among women worldwide, is not well established. Among studies exploring associations of viruses with breast cancer, potential linkages have been identified between breast cancer and five viruses: beta retrovirus, (i.e., mouse mammary tumor virus), human papillomavirus, Epstein Barr virus. bovine leukemia virus, and human cytomegalovirus.

METHODS

In this review, we provide a comprehensive evaluation of epidemiological ecologic, case-control, case-only, and cohort studies investigating these associations. We discuss results from several existing reviews and meta-analyses, evaluate epidemiological studies published in the past five years, and assess the relationship between these viruses and breast tumor clinicopathological factors.

RESULTS

The strongest epidemiological evidence for a viral role in breast cancer exists for MMTV and HPV, though limitations include lack of prospective studies for MMTV and potential detection bias in HPV studies. Viral detection challenges have limited studies of EBV and HCMV. Fewer studies have evaluated BLV, and though it has been associated with higher risk of breast cancer, sample sizes are quite small.   CONCLUSION: While epidemiologic evidence exists for an association between these five viruses and breast cancer, various methodological issues and lack of prospective studies preclude robust conclusions. Future research should prioritize establishing a temporal relationship between infection and disease, minimizing misclassification of detection assays, and further exploring the influence of co-infections.

A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma

Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumor cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analyzed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms.

Inflammatory breast cancer microenvironment repertoire based on DNA methylation data deconvolution reveals actionable targets to enhance the treatment efficacy

BACKGROUND

Although the clinical signs of inflammatory breast cancer (IBC) resemble acute inflammation, the role played by infiltrating immune and stromal cells in this aggressive disease is uncharted. The tumor microenvironment (TME) presents molecular alterations, such as epimutations, prior to morphological abnormalities. These changes affect the distribution and the intricate communication between the TME components related to cancer prognosis and therapy response. Herein, we explored the global DNA methylation profile of IBC and surrounding tissues to estimate the microenvironment cellular composition and identify epigenetically dysregulated markers.

METHODS

We used the HiTIMED algorithm to deconvolve the bulk DNA methylation data of 24 IBC and six surrounding non-tumoral tissues (SNT) (GSE238092) and determine their cellular composition. The prognostic relevance of cell types infiltrating IBC and their relationship with clinicopathological variables were investigated. CD34 (endothelial cell marker) and CD68 (macrophage marker) immunofluorescence staining was evaluated in an independent set of 17 IBC and 16 non-IBC samples.

RESULTS

We found lower infiltration of endothelial, stromal, memory B, dendritic, and natural killer cells in IBC than in SNT samples. Higher endothelial cell (EC) and stromal cell content were related to better overall survival. EC proportions positively correlated with memory B and memory CD8+ T infiltration in IBC. Immune and EC markers exhibited distinct DNA methylation profiles between IBC and SNT samples, revealing hypermethylated regions mapped to six genes (CD40, CD34, EMCN, HLA-G, PDPN, and TEK). We identified significantly higher CD34 and CD68 protein expression in IBC compared to non-IBC.

CONCLUSIONS

Our findings underscored cell subsets that distinguished patients with better survival and dysregulated markers potentially actionable through combinations of immunotherapy and epigenetic drugs.

Multi-regional sequencing reveals the genetic and immune heterogeneity of non-cancerous tissues in gastric cancer

Gastric cancer (GC) is one of the most heterogeneous tumors. However, research on normal tissue adjacent to the tumor (NAT) is very limited. We performed multi-regional omics sequencing on 150 samples to assess the genetic basis and immune microenvironment in NAT and matched primary tumor or lymph node metastases. NATs demonstrated different mutated genes compared with GC, and NAT genomes underwent independent evolution with low variant allele frequency. Mutation profiles were predominated by aging and smoking-associated signatures in NAT instead of signatures associated with genetic instability. Although the immune microenvironment within NATs shows substantial intra-patient heterogeneity, the proportion of shared TCR clones among NATs is five times higher than that of tumor regions. These findings support the notion that subclonal expansion is not pronounced in NATs. We also demonstrated remarkable intra-patient heterogeneity of GCs and revealed heterogeneity of focal amplification of CD274 (encoding PD-L1) that leads to differential expression. Finally, we identified that monoclonal seeding is predominant in GC, which is followed by metastasis-to-metastasis dissemination in individual lymph nodes. These results provide novel insights into GC carcinogenesis. © 2024 The Pathological Society of Great Britain and Ireland.

Single-nucleus and spatial transcriptome reveal adrenal homeostasis in normal and tumoural adrenal glands

The human adrenal gland is a complex endocrine tissue. Studies on adrenal renewal have been limited to animal models or human foetuses. Enhancing our understanding of adult human adrenal homeostasis is crucial for gaining insights into the pathogenesis of adrenal diseases, such as adrenocortical tumours. Here, we present a comprehensive cellular genomics analysis of the adult human normal adrenal gland, combining single-nuclei RNA sequencing and spatial transcriptome data to reconstruct adrenal gland homeostasis. As expected, we identified primary cells of the various zones of the adrenal cortex and medulla, but we also uncovered additional cell types. They constitute the adrenal microenvironment, including immune cells, mostly composed of a large population of M2 macrophages, and new cell populations, including different subpopulations of vascular-endothelial cells and cortical-neuroendocrine cells. Utilizing spatial transcriptome and pseudotime trajectory analysis, we support evidence of the centripetal dynamics of adrenocortical cell maintenance and the essential role played by Wnt/β-catenin, sonic hedgehog, and fibroblast growth factor pathways in the adult adrenocortical homeostasis. Furthermore, we compared single-nuclei transcriptional profiles obtained from six healthy adrenal glands and twelve adrenocortical adenomas. This analysis unveiled a notable heterogeneity in cell populations within the adenoma samples. In addition, we identified six distinct adenoma-specific clusters, each with varying distributions based on steroid profiles and tumour mutational status. Overall, our results provide novel insights into adrenal homeostasis and molecular mechanisms potentially underlying early adrenocortical tumorigenesis and/or autonomous steroid secretion. Our cell atlas represents a powerful resource to investigate other adrenal-related pathologies.

Atorvastatin lowers breast cancer risk by reversing an early tumorigenic signature

Breast cancer remains a significant health challenge with complex molecular mechanisms. While many studies have explored genetic markers in breast carcinogenesis, few have studied the potential impact of pharmacological interventions such as Atorvastatin on its genetic landscape. This study aimed to elucidate the molecular distinctions between normal and tumor-adjacent tissues in breast cancer and to investigate the potential protective role of atorvastatin, primarily known for its lipid-lowering effects, against breast cancer. Searching the Gene Expression Omnibus database identified two datasets, GSE9574 and GSE20437, comparing normal breast tissues with tumor-adjacent samples, which were merged, and one dataset, GSE63427, comparing paired pre- and post-treated patients with atorvastatin. Post-ComBat application showed merged datasets' consistency, revealing 116 DEGs between normal and tumor-adjacent tissues. Although initial GSE63427 data analysis suggested a minimal impact of atorvastatin, 105 DEGs post-treatment were discovered. Thirteen genes emerged as key players, both affected by Atorvastatin and dysregulated in tumor-adjacent tissues. Pathway analysis spotlighted the significance of these genes in processes like inflammation, oxidative stress, apoptosis, and cell cycle control. Moreover, there was a noticeable interaction between these genes and the immunological microenvironment in tumor-adjacent tissues, with Atorvastatin potentially altering the suppressive immune landscape to favor anti-tumor immunity. Survival analysis further highlighted the prognostic potential of the 13-gene panel, with 12 genes associated with improved survival outcomes. The 13-gene signature offers promising insights into breast cancer's molecular mechanisms and atorvastatin's potential therapeutic role. The preliminary findings advocate for an in-depth exploration of atorvastatin's impact on.

Epithelial-mesenchymal transition associated markers in sarcomatoid transformation of clear cell renal cell carcinoma

Epithelial-mesenchymal transition (EMT) plays a pivotal role in the development and progression of many cancers. Partial EMT (pEMT) could represent a critical step in tumor migration and dissemination. Sarcomatoid renal cell carcinoma (sRCC) is an aggressive form of renal cell carcinoma (RCC) composed of a carcinomatous (sRCC-Ca) and sarcomatous (sRCC-Sa) component. The role of (p)EMT in the progression of RCC to sRCC remains unclear. The aim of this study was to investigate the involvement of (p)EMT in RCC and sRCC. Tissue samples from 10 patients with clear cell RCC (ccRCC) and 10 patients with sRCC were selected. The expression of main EMT markers (miR-200 family, miR-205, SNAI1/2, TWIST1/2, ZEB1/2, CDH1/2, VIM) was analyzed by qPCR in ccRCC, sRCC-Ca, and sRCC-Sa and compared to non-neoplastic tissue and between both groups. Expression of E-cadherin, N-cadherin, vimentin and ZEB2 was analyzed using immunohistochemistry. miR-200c was downregulated in sRCC-Ca compared to ccRCC, while miR-200a was downregulated in sRCC-Sa compared to ccRCC. CDH1 was downregulated in sRCC-Sa when compared to any other group. ZEB2 was downregulated in ccRCC and sRCC compared to corresponding non-neoplastic kidney. A positive correlation was observed between CDH1 expression and miR-200a/b/c. Our results suggest that full EMT is not present in sRCC. Instead, discreet molecular differences exist between ccRCC, sRCC-Ca, and sRCC-Sa, possibly representing distinct intermediary states undergoing pEMT.

Discovery and validation of combined biomarkers for the diagnosis of esophageal intraepithelial neoplasia and esophageal squamous cell carcinoma

Early diagnosis and intervention of esophageal squamous cell carcinoma (ESCC) can improve the prognosis. The purpose of this study was to identify biomarkers for ESCC and esophageal precancerous lesions (intraepithelial neoplasia, IEN). Based on the proteomic and genomic data of esophageal tissue including previously reported data, up-regulated proteins with copy number amplification in esophageal cancer were screened as candidate biomarkers. Five proteins, including KDM2A, RAD9A, ECT2, CYHR1 and TONSL, were confirmed by immunohistochemistry on ESCC and normal esophagus (NE). Then, we investigated the expression of 5 proteins in 236 participants (60 NEs, 93 IENs and 83 ESCCs) which were randomly divided into training set and test set. When distinguishing ESCC from NE, the area under curve (AUC) of the multiprotein model was 0.940 in the training set, while the lowest AUC of a protein was 0.735. In the test set, the results were similar. When distinguishing ESCC from IEN or distinguishing IEN from NE, the diagnostic efficiency of the multi-protein models were also improved compared with that of single protein. Our findings suggest that combined detection of KDM2A, RAD9A, ECT2, CYHR1 and TONSL can be used as potential biomarkers for the early diagnosis of ESCC and precancerous lesion development prediction. SIGNIFICANCE: Candidate biomarkers including KDM2A, RAD9A, ECT2, CYHR1 and TONSL screened by integrating genomic and proteomic data from the esophagus can be used as potential biomarkers for the early diagnosis of esophageal squamous cell carcinoma and precancerous lesion development prediction.

Changes in the Expression of Genes Regulating the Response to Hypoxia, Inflammation, Cell Cycle, Apoptosis, and Epithelial Barrier Functioning during Colitis-Associated Colorectal Cancer Depend on Individual Hypoxia Tolerance

One of the factors contributing to colorectal cancer (CRC) development is inflammation, which is mostly hypoxia-associated. This study aimed to characterize the morphological and molecular biological features of colon tumors in mice that were tolerant and susceptible to hypoxia based on colitis-associated CRC (CAC). Hypoxia tolerance was assessed through a gasping time evaluation in a decompression chamber. One month later, the animals were experimentally modeled for colitis-associated CRC by intraperitoneal azoxymethane administration and three dextran sulfate sodium consumption cycles. The incidence of tumor development in the distal colon in the susceptible to hypoxia mice was two times higher and all tumors (100%) were represented by adenocarcinomas, while in the tolerant mice, only 14% were adenocarcinomas and 86% were glandular intraepithelial neoplasia. The tumor area assessed on serially stepped sections was statistically significantly higher in the susceptible animals. The number of macrophages, CD3-CD19+, CD3+CD4+, and NK cells in tumors did not differ between animals; however, the number of CD3+CD8+ and vimentin+ cells was higher in the susceptible mice. Changes in the expression of genes regulating the response to hypoxia, inflammation, cell cycle, apoptosis, and epithelial barrier functioning in tumors and the peritumoral area depended on the initial mouse's hypoxia tolerance, which should be taken into account for new CAC diagnostics and treatment approaches development.

Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes

BACKGROUND

The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes.

RESULTS

We studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin.

CONCLUSION

We show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

A positive feedback loop between PFKP and c-Myc drives head and neck squamous cell carcinoma progression

BACKGROUND

The aberrant expression of phosphofructokinase-platelet (PFKP) plays a crucial role in the development of various human cancers by modifying diverse biological functions. However, the precise molecular mechanisms underlying the role of PFKP in head and neck squamous cell carcinoma (HNSCC) are not fully elucidated.

METHODS

We assessed the expression levels of PFKP and c-Myc in tumor and adjacent normal tissues from 120 HNSCC patients. A series of in vitro and in vivo experiments were performed to explore the impact of the feedback loop between PFKP and c-Myc on HNSCC progression. Additionally, we explored the therapeutic effects of targeting PFKP and c-Myc in HNSCC using Patient-Derived Organoids (PDO), Cell Line-Derived Xenografts, and Patients-Derived Xenografts.

RESULTS

Our findings indicated that PFKP is frequently upregulated in HNSCC tissues and cell lines, correlating with poor prognosis. Our in vitro and in vivo experiments demonstrate that elevated PFKP facilitates cell proliferation, angiogenesis, and metastasis in HNSCC. Mechanistically, PFKP increases the ERK-mediated stability of c-Myc, thereby driving progression of HNSCC. Moreover, c-Myc stimulates PFKP expression at the transcriptional level, thus forming a positive feedback loop between PFKP and c-Myc. Additionally, our multiple models demonstrate that co-targeting PFKP and c-Myc triggers synergistic anti-tumor effects in HNSCC.

CONCLUSION

Our study demonstrates the critical role of the PFKP/c-Myc positive feedback loop in driving HNSCC progression and suggests that simultaneously targeting PFKP and c-Myc may be a novel and effective therapeutic strategy for HNSCC.

Ductal carcinoma in situ develops within clonal fields of mutant cells in morphologically normal ducts

Mutations are abundantly present in tissues of healthy individuals, including the breast epithelium. Yet it remains unknown whether mutant cells directly induce lesion formation or first spread, leading to a field of mutant cells that is predisposed towards lesion formation. To study the clonal and spatial relationships between morphologically normal breast epithelium adjacent to pre-cancerous lesions, we developed a three-dimensional (3D) imaging pipeline combined with spatially resolved genomics on archival, formalin-fixed breast tissue with the non-obligate breast cancer precursor ductal carcinoma in situ (DCIS). Using this 3D image-guided characterization method, we built high-resolution spatial maps of DNA copy number aberration (CNA) profiles within the DCIS lesion and the surrounding normal mammary ducts. We show that the local heterogeneity within a DCIS lesion is limited. However, by mapping the CNA profiles back onto the 3D reconstructed ductal subtree, we find that in eight out of 16 cases the healthy epithelium adjacent to the DCIS lesions has overlapping structural variations with the CNA profile of the DCIS. Together, our study indicates that pre-malignant breast transformations frequently develop within mutant clonal fields of morphologically normal-looking ducts. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.