A pathology atlas of the human cancer transcriptome

Muc16CD is a novel CAR T cell target antigen for the treatment of pancreatic cancer

Pancreatic cancer is an aggressive malignancy with a 5-year survival rate of 13% that remains refractory to current immunotherapies, such as chimeric antigen receptor (CAR) T cells. These engineered cells can produce robust anti-tumor responses but require a reliable tumor-associated antigen (TAA) target. Here, we describe the retained ectodomain of Muc16, Muc16CD, as a novel TAA for targeting by CAR T cell therapy in pancreatic cancer. We establish clinically relevant, endogenous Muc16 and Muc16CD expression in pancreatic tumor tissues for CAR T cell targeting. Muc16CD-directed CAR T cells can both recognize and activate in a polyfunctional manner in response to patient-derived pancreatic tumor cells. Last, we demonstrate that Muc16CD-directed CAR T cells can elicit an anti-tumor response in vivo with significantly enhanced tumor control and survival benefits in a pancreatic tumor model. Overall, these findings demonstrate the utility of Muc16CD-targeted CAR T cell therapy in the novel setting of pancreatic cancer.

Mathematical modelling and deep learning algorithms to automate assessment of single and digitally multiplexed immunohistochemical stains in tumoural stroma

Whilst automated analysis of immunostains in pathology research has focused predominantly on the epithelial compartment, automated analysis of stains in the stromal compartment is challenging and therefore requires time-consuming pathological input and guidance to adjust to tissue morphometry as perceived by pathologists. This study aimed to develop a robust method to automate stromal stain analyses using 2 of the commonest stromal stains (SMA and desmin) employed in clinical pathology practice as examples. An effective computational method capable of automatically assessing and quantifying tumour-associated stromal stains was developed and applied on cores of colorectal cancer tissue microarrays. The methodology combines both mathematical models and deep learning techniques with the former requiring no training data and the latter as many inputs as possible. The novel mathematical model was used to produce a digital double marker overlay allowing for fast automated digital multiplex analysis of stromal stains. The results show that deep learning methodologies in combination with mathematical modelling allow for an accurate means of quantifying stromal stains whilst also opening up new possibilities of digital multiplex analyses.

Effect of ubiquitin-specific proteinase 43 on ovarian serous adenocarcinoma and its clinical significance

BACKGROUND

Ovarian cancer stands as a highly aggressive malignancy. The core aim of this investigation is to uncover genes pivotal to the progression and prognosis of ovarian cancer, while delving deep into the intricate mechanisms that govern their impact.

METHODS

The study entailed the retrieval of RNA-seq data and survival data from the XENA database. Outliers were meticulously excluded in accordance with TCGA guidelines and through principal components analysis. The R package 'deseq2' was harnessed to extract differentially expressed genes. WGCNA was employed to prioritise these genes, and Cox regression analysis and survival analysis based on disease-specific time were conducted to identify significant genes. Immunohistochemistry validation was undertaken to confirm the distinct expression of USP43. Furthermore, the influence of USP43 on the biological functions of ovarian cancer cells was explored using techniques such as RNA interference, western blotting, scratch assays, and matrigel invasion assays. The examination of immune infiltration was facilitated via CIBERSORT.

RESULTS

The study unearthed 5195 differentially expressed genes between ovarian cancer and normal tissue, comprising 3416 up-regulated and 1779 down-regulated genes. WGCNA pinpointed 204 genes most intimately tied to tumorigenesis. The previously undisclosed gene USP43 exhibited heightened expression in tumour tissues and exhibited associations with overall survival and disease-specific survival. USP43 emerged as a driver of cell migration (43.27 ± 3.91% vs 19.69 ± 1.94%) and invasion ability (314 ± 32 vs 131 ± 12) through the mechanism of epithelial mesenchymal transition, potentially mediated by the KRAS pathway. USP43 was also identified as a booster of CD4+ T memory resting cell infiltration, while concurrently reducing M1 macrophages within cancer, thereby fostering a milieu with relatively immune suppressive traits. Interestingly, USP43 demonstrated connections with epigenetically regulated-mRNAsi, although not with mRNAsi.

CONCLUSION

This study underscores the role of USP43 in facilitating tumour migration and invasion. It postulates USP43 as a novel therapeutic target for ovarian cancer treatment.

Comprehensive pan-cancer analysis unveils the significant prognostic value and potential role in immune microenvironment modulation of TRIB3

TRIB3, a pseudokinase, was previously studied within only some specific cancer types, leaving its comprehensive functions in pan-cancer contexts largely unexplored. Here, we performed an integrated analysis of TRIB3 expression, prognosis, genetic alterations, functional enrichment and tumor immune-related characteristics in 33 cancer types. Our results showed that TRIB3 exhibits high expression levels across 24 different cancer types and correlates closely with unfavorable prognoses. Meanwhile, TRIB3 shows mutations in a wide spectrum of 22 distinct cancer types, with the predominant mutation types being missense mutations and gene amplifications, and significant changes in DNA methylation levels in 14 types of cancer. We further discovered that TRIB3 expression is significantly associated with cancer immune-related genome mutations, such as tumor mutational burden (TMB), microsatellite instability (MSI) and DNA mismatch repair (MMR), and infiltration of immunosuppressive cells, such as CD4+ Th2 cells and myeloid-derived suppressor cells (MDSCs), into the tumor microenvironment. These results indicated that the expression of TRIB3 might reshape the tumor immune microenvironment (TIME) and lead to immunosuppressive "cold" tumors. In addition, our results confirmed that the loss of function of TRIB3 inhibits cell proliferation, promotes apoptosis, and leads to significant enrichment of "hot" tumor-related immune pathways, at least in breast cancer cells, which further supports the important role of TRIB3 in cancer prognosis and TIME regulation. Together, this pan-cancer investigation provided a comprehensive understanding of the critical role of TRIB3 in human cancers, and suggested that TRIB3 might be a promising prognostic biomarker and a potential target for cancer immunotherapy.

Computational pathology: A survey review and the way forward

Computational Pathology (CPath) is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main objective for CPath is to develop infrastructure and workflows of digital diagnostics as an assistive CAD system for clinical pathology, facilitating transformational changes in the diagnosis and treatment of cancer that are mainly address by CPath tools. With evergrowing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article we provide a comprehensive review of more than 800 papers to address the challenges faced in problem design all-the-way to the application and implementation viewpoints. We have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. We hope this helps the community to locate relevant works and facilitate understanding of the field's future directions. In a nutshell, we oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. We overview this cycle from different perspectives of data-centric, model-centric, and application-centric problems. We finally sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath. For updated information on this survey review paper and accessing to the original model cards repository, please refer to GitHub. Updated version of this draft can also be found from arXiv.

Highly efficient generation of self-renewing trophoblast from human pluripotent stem cells

Human pluripotent stem cells (hPSCs) represent a powerful model system to study early developmental processes. However, lineage specification into trophectoderm (TE) and trophoblast (TB) differentiation remains poorly understood, and access to well-characterized placental cells for biomedical research is limited, largely depending on fetal tissues or cancer cell lines. Here, we developed novel strategies enabling highly efficient TE specification that generates cytotrophoblast (CTB) and multinucleated syncytiotrophoblast (STB), followed by the establishment of trophoblast stem cells (TSCs) capable of differentiating into extravillous trophoblast (EVT) and STB after long-term expansion. We confirmed stepwise and controlled induction of lineage- and cell-type-specific genes consistent with developmental biology principles and benchmarked typical features of placental cells using morphological, biochemical, genomics, epigenomics, and single-cell analyses. Charting a well-defined roadmap from hPSCs to distinct placental phenotypes provides invaluable opportunities for studying early human development, infertility, and pregnancy-associated diseases.

Deciphering the multi-scale mechanism of herbal phytoconstituents in targeting breast cancer: a computational pharmacological perspective

Breast Cancer (BC) is the most common cause of cancer-associated deaths in females worldwide. Despite advancements in BC treatment driven by extensive characterization of its molecular hallmarks, challenges such as drug resistance, tumor relapse, and metastasis persist. Therefore, there is an urgent need for alternative treatment approaches with multi-modal efficacy to overcome these hurdles. In this context, natural bioactives are increasingly recognized for their pivotal role as anti-cancer compounds. This study focuses on predicting molecular targets for key herbal phytoconstituents-gallic acid, piperine, quercetin, resveratrol, and beta-sitosterol-present in the polyherbal formulation, Krishnadi Churna. Using an in-silico network pharmacology model, key genes were identified and docked against these marker compounds and controls. Mammary carcinoma emerged as the most significant phenotype of the putative targets. Analysis of an online database revealed that out of 135 predicted targets, 134 were mutated in breast cancer patients. Notably, ESR1, CYP19A1, and EGFR were identified as key genes which are known to regulate the BC progression. Docking studies demonstrated that the herbal phytoconstituents had similar or better docking scores than positive controls for these key genes, with convincing protein-ligand interactions confirmed by molecular dynamics simulations, MM/GBSA and free energy landscape (FEL) analysis. Overall, this study highlights the predictive potential of herbal phytoconstituents in targeting BC genes, suggesting their promise as a basis for developing new therapeutic formulations for BC.

Same Day Access to Folded Synthetic Proteins

Understanding protein function is a cornerstone of modern biology. Research centers worldwide dedicate significant efforts to prepare individual proteins for study, the isolation and purification of which can take days to months. We developed a workflow that enables same-day access to functional synthetic proteins. Chemical synthesis provides access to crude protein chains in hours, but the removal of the synthetic side products is typically a days-long process. We find that chemical modifications on side products lead to significant and unpredictable changes in the folding behavior. Consistent with these findings, we discovered that approaches based on biophysical properties characteristic of the folded protein target can discriminate against chemically similar species. Confirming our protocol with nine protein targets, we show that appropriate desalting followed by different folding strategies enables isolation of functional single-domain proteins in hours instead of days. Each target was isolated in under 10 h, including some proteins with post-translational modifications, non-natural amino acids, and disulfide bonds. Rapid biological discovery requires on-demand access to proteins, and the folding pipeline described here is uniquely suited to enabling these efforts. The folding process presented here was not assessed on complex proteins, and therefore, it may require further optimization in those cases.

DEK regulates B-cell proliferative capacity and is associated with aggressive disease in low-grade B-cell lymphomas

This study sheds light on the pivotal role of the oncoprotein DEK in B-cell lymphoma. We reveal DEK expression correlates with increased tumor proliferation and inferior overall survival in cases diagnosed with low-grade B-cell lymphoma (LGBCL). We also found significant correlation between DEK expression and copy number alterations in LGBCL tumors, highlighting a novel mechanism of LGBCL pathogenesis that warrants additional exploration. To interrogate the mechanistic role of DEK in B-cell lymphoma, we generated a DEK knockout cell line model, which demonstrated DEK depletion caused reduced proliferation and altered expression of key cell cycle and apoptosis-related proteins, including Bcl-2, Bcl-xL, and p53. Notably, DEK depleted cells showed increased sensitivity to apoptosis-inducing agents, including venetoclax and staurosporine, which underscores the therapeutic potential of targeting DEK in B-cell lymphomas. Overall, our study contributes to a better understanding of DEK's role as an oncoprotein in B-cell lymphomas, highlighting its potential as both a promising therapeutic target and a novel biomarker for aggressive LGBCL. Further research elucidating the molecular mechanisms underlying DEK-mediated tumorigenesis could pave the way for improved treatment strategies and better clinical outcomes for patients with B-cell lymphoma.

Siah3 acts as a physiological mitophagy suppressor that facilitates axonal degeneration

Mitophagy eliminates dysfunctional mitochondria, and defects in this cellular housekeeping mechanism are implicated in various age-related diseases. Here, we found that mitophagy suppression by the protein Siah3 promoted developmental axonal remodeling in mice. Siah3-deficient mice displayed increased peripheral sensory innervation. Cultured Siah3-deficient sensory neurons exhibited delays in both axonal degeneration and caspase-3 activation in response to withdrawal of nerve growth factor. Mechanistically, Siah3 was transcriptionally induced by the loss of trophic support and formed a complex with the cytosolic E3 ubiquitin ligase parkin, a core component of mitophagy, in transfected cells. Axons of Siah3-deficient neurons mounted profound mitophagy upon initiation of degeneration but not under basal conditions. Neurons lacking both Siah3 and parkin did not exhibit the delay in trophic deprivation-induced axonal degeneration or the induction of axonal mitophagy that was seen in Siah3-deficient neurons. Our findings reveal that mitophagy regulation acts as a gatekeeper of a physiological axon elimination program.

Pan-cancer analysis of the prognostic and immunological roles of SHP-1/ptpn6

SHP-1, a nonreceptor protein tyrosine phosphatase encoded by ptpn6, has been regarded as a regulatory protein of hematopoietic cell biology for years. However, there is now increasing evidence to support its role in tumors. Thus, the role of ptpn6 for prognosis and immune regulation across 33 tumors was investigated, aiming to explore its functional heterogeneity and clinical significance in pan-cancer. Differential expression of ptpn6 was found between cancer and adjacent normal tissues, and its expression was significantly correlated with the prognosis of tumor patients. In most cancers, ptpn6 expression was significantly associated with immune infiltration. This was further confirmed by ptpn6-related genes/proteins enrichment analysis. Additionally, genetic alterations in ptpn6 was observed in most cancers. As for epigenetic changes, it's phosphorylation levels significantly altered in 6 tumors, while methylation levels significantly altered in 12 tumors. Notably, the methylation levels of ptpn6 were significantly decreased in 11 tumors, accompanied by its increased expression in 8 of them, suggesting that the hypomethylation may be related to its increased expression. Our results show that ptpn6 plays a specific role in tumor immunity and exerts a pleiotropic effect in a variety of tumors. It can serve as a prognostic factor for some cancers. Especially in LGG, KIRC, UCS and TGCT, the increased expression of ptpn6 is associated with poor prognosis and high immune infiltration. This aids in understanding the role of ptpn6 in tumor biology, and can provide insight into presenting a potential biomarker for poor prognosis and immune infiltration in cancers.

SLC45A4 is involved in malignant progression of ovarian cancer through glycolytic metabolic reprogramming

Tumor cells promote malignant behaviors such as proliferation, invasion, and metastasis of cancer cells through glucose metabolic reprogramming, but the role of the H-dependent sugar cotransporter SLC45A4 in regulating metabolic reprogramming in ovarian cancer (OC) remains largely unknown. This study aimed to investigate the effects of SLC45A4 silencing on the transcriptome spectrum of ovarian cancer cells (OCC), glucose uptake, lactic acid production, intracellular ATP levels, and the expression and activity of HIF-α glycolysis signaling pathway. The results showed that SLC45A4 is overexpressed in OC and its elevated expression correlates with adverse clinical outcomes in OC patients. Silencing of SLC45A4 significantly inhibited the proliferation, invasion, and metastasis of OCC by suppressing glucose uptake and glycolysis, and it also reduced the expression of HIF-α glycolysis signaling pathway in OC tissues. In vivo experiments using shRNA to knock down SLC45A4 in xenograft models in nude mice demonstrated a significant inhibition of tumor growth. These findings suggest that SLC45A4 silencing can restrain the malignant progression of OC by inhibiting glucose uptake in OCC and affecting the reprogramming of glycolytic energy metabolism, indicating that SLC45A4 may serve as a potential therapeutic target for OC intervention.

Human DUS1L catalyzes dihydrouridine modification at tRNA positions 16/17, and DUS1L overexpression perturbs translation

Human cytoplasmic tRNAs contain dihydrouridine modifications at positions 16 and 17 (D16/D17). The enzyme responsible for D16/D17 formation and its cellular roles remain elusive. Here, we identify DUS1L as the human tRNA D16/D17 writer. DUS1L knockout in the glioblastoma cell lines LNZ308 and U87 causes loss of D16/D17. D formation is reconstituted in vitro using recombinant DUS1L in the presence of NADPH or NADH. DUS1L knockout/overexpression in LNZ308 cells shows that DUS1L supports cell growth. Moreover, higher DUS1L expression in glioma patients is associated with poorer prognosis. Upon vector-mediated DUS1L overexpression in LNZ308 cells, 5' and 3' processing of precursor tRNATyr(GUA) is inhibited, resulting in a reduced mature tRNATyr(GUA) level, reduced translation of the tyrosine codons UAC and UAU, and reduced translational readthrough of the near-cognate stop codons UAA and UAG. Moreover, DUS1L overexpression increases the amounts of several D16/D17-containing tRNAs and total cellular translation. Our study identifies a human dihydrouridine writer, providing the foundation to study its roles in health and disease.

The Diagnostic and Prognostic Value of Neurotransmitter Receptor-Related Genes in Colon Adenocarcinoma

Colorectal cancer (CRC) is a malignant tumor with high morbidity and mortality in the world. This study aimed to find receptor-related genes (NRGs) with diagnostic and prognostic value in colon adenocarcinoma (COAD). The Cancer Genome Atlas (TCGA) and the Human Protein Atlas database databases were applied to find differential expression NRGs between COAD and normal colonic tissues. Subsequently, Cox regression analysis and minimum absolute contraction and selection operator algorithm were used to construct a prognosis nomogram based on TCGA and Gene Expression Omnibus databases. Expression levels of 35 NRGs were significant differences in COAD and normal colonic tissues. ROC curves showed that 24 NRGs had high diagnostic accuracy (AUC > 0.850) in COAD. Risk score was constructed based on 10 NRGs for the first time. Cox regression analysis revealed risk score was an independent risk factor and a higher risk score predicts a later TNM stage. Finally, a prognostic nomogram containing risk score and clinical features was established. Calibration curves and C-index suggested the powerful predictable value of the model. This study identified the NRGs with diagnostic value and prognostic value, providing a direction for treatment of COAD patients.

A proteomic approach supports the clinical relevance of TAT-Cx43266-283 in glioblastoma

Glioblastoma (GBM) is the most frequent and aggressive primary brain cancer. The Src inhibitor, TAT-Cx43266-283, exerts antitumor effects in in vitro and in vivo models of GBM. Because addressing the mechanism of action is essential to translate these results to a clinical setting, in this study we carried out an unbiased proteomic approach. Data-independent acquisition mass spectrometry proteomics allowed the identification of 190 proteins whose abundance was modified by TAT-Cx43266-283. Our results were consistent with the inhibition of Src as the mechanism of action of TAT-Cx43266-283 and unveiled antitumor effectors, such as p120 catenin. Changes in the abundance of several proteins suggested that TAT-Cx43266-283 may also impact the brain microenvironment. Importantly, the proteins whose abundance was reduced by TAT-Cx43266-283 correlated with an improved GBM patient survival in clinical datasets and none of the proteins whose abundance was increased by TAT-Cx43266-283 correlated with shorter survival, supporting its use in clinical trials.

High-Throughput Transcriptomics Screen of ToxCast Chemicals in U-2 OS Cells

New approach methodologies (NAMs) aim to accelerate the pace of chemical risk assessment while simultaneously reducing cost and dependency on animal studies. High Throughput Transcriptomics (HTTr) is an emerging NAM in the field of chemical hazard evaluation for establishing in vitro points-of-departure and providing mechanistic insight. In the current study, 1201 test chemicals were screened for bioactivity at eight concentrations using a 24-h exposure duration in the human- derived U-2 OS osteosarcoma cell line with HTTr. Assay reproducibility was assessed using three reference chemicals that were screened on every assay plate. The resulting transcriptomics data were analyzed by aggregating signal from genes into signature scores using gene set enrichment analysis, followed by concentration-response modeling of signatures scores. Signature scores were used to predict putative mechanisms of action, and to identify biological pathway altering concentrations (BPACs). BPACs were consistent across replicates for each reference chemical, with replicate BPAC standard deviations as low as 5.6 × 10-3 μM, demonstrating the internal reproducibility of HTTr-derived potency estimates. BPACs of test chemicals showed modest agreement (R2 = 0.55) with existing phenotype altering concentrations from high throughput phenotypic profiling using Cell Painting of the same chemicals in the same cell line. Altogether, this HTTr based chemical screen contributes to an accumulating pool of publicly available transcriptomic data relevant for chemical hazard evaluation and reinforces the utility of cell based molecular profiling methods in estimating chemical potency and predicting mechanism of action across a diverse set of chemicals.

Overexpression of SEZ6L2 and Immune Infiltration in Cancer Based on Gene Image Diagnosis

BACKGROUND

With the rapid advancement of optical image diagnostic technology, researchers are delving into the potential applications in the field of cancer diagnosis and treatment. The exact link between the SEZ6L2 gene and cancer immune infiltration remains elusive.

MATERIALS AND METHODS

This study aims to investigate the relationship between SEZ6L2 gene overexpression and cancer immune infiltration using optical image diagnostic technology, thereby presenting novel insights for enhancing cancer diagnosis and treatment strategies. Tissue samples obtained from cancer patients were meticulously analyzed to quantitatively assess the expression of the SEZ6L2 gene through light image diagnostic technology. Additionally, immunohistochemical techniques were employed to assess the nature and quantity of immune infiltrating cells within the cancerous tissues.

RESULTS

The enrichment pathways were found to include complement activation, circulating immunoglobulin mediated humoral immune response, protein activation cascade, immunoglobulin complex, and immunoglobulin. In addition, the expression of SEZ6L2 is closely related to the infiltration level of tumor infiltrating immune cells (TIICs), and there is a potential relationship between the expression of SEZ6L2 and different marker genes of TIIC.

CONCLUSION

Increased SEZ6L2 mRNA expression in breast invasive carcinoma was significantly associated with negative prognosis and immune invasion. SEZ6L2 may be a novel prognostic biomarker and a potential immunotherapeutic target in BRCA.

5-Hydroxymethylated Biomarkers in Cell-Free DNA Predict Occult Colorectal Cancer up to 36 Months Before Diagnosis in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial

PURPOSE

Using the prostate, lung, colorectal, and ovarian (PLCO) Cancer Screening Trial samples, we identified cell-free DNA (cfDNA) candidate biomarkers bearing the epigenetic mark 5-hydroxymethylcytosine (5hmC) that detected occult colorectal cancer (CRC) up to 36 months before clinical diagnosis.

MATERIALS AND METHODS

We performed the 5hmC-seal assay and sequencing on ≤8 ng cfDNA extracted from PLCO study participant plasma samples, including n = 201 cases (diagnosed with CRC within 36 months of blood collection) and n = 401 controls (no cancer diagnosis on follow-up). We conducted association studies and machine learning modeling to analyze the genome-wide 5hmC profiles within training and validation groups that were randomly selected at a 2:1 ratio.

RESULTS

We successfully obtained 5hmC profiles from these decades-old samples. A weighted Cox model of 32 5hmC-modified gene bodies showed a predictive detection value for CRC as early as 36 months before overt tumor diagnosis (training set AUC, 77.1% [95% CI, 72.2 to 81.9] and validation set AUC, 72.8% [95% CI, 65.8 to 79.7]). Notably, the 5hmC-based predictive model showed comparable performance regardless of sex and race/ethnicity, and significantly outperformed risk factors such as age and obesity (assessed as BMI). Finally, when splitting cases at median weighted prediction scores, Kaplan-Meier analyses showed significant risk stratification for CRC occurrence in both the training set (hazard ratio, [HR], 3.3 [95% CI, 2.6 to 5.8]) and validation set (HR, 3.1 [95% CI, 1.8 to 5.8]).

CONCLUSION

Candidate 5hmC biomarkers and a scoring algorithm have the potential to predict CRC occurrence despite the absence of clinical symptoms and effective predictors. Developing a minimally invasive clinical assay that detects 5hmC-modified biomarkers holds promise for improving early CRC detection and ultimately patient outcomes.

Increased SEC14L2 expression is associated with clinicopathological features and worse prognosis in oral squamous cell carcinoma

Abnormal expression of SEC14L2 has been implicated in many human cancers. However, the role of SEC14L2 in oral squamous cell carcinoma (OSCC) remains unclear. Therefore, this study aimed to evaluate the expression and prognostic roles of SEC14L2 in OSCC. OSCC tumors and adjacent non-tumors were collected from OSCC patients and used for SEC14L2 mRNA expression by quantitative reverse transcription PCR (RT-qPCR). Additionally, the expression of SEC14L2 was further analyzed using The Cancer Genome Atlas-Head Neck Squamous Cell Carcinoma (TCGA-HNSCC) dataset to identify its relationship with HNSCC clinical characteristics. The Kaplan-Meier plot was used to assess survival rates, and the Tumor Immune Estimation Resource (TIMER) database was used to examine the correlation between SEC14L2 expression and tumor immune cell infiltration. In silico tools also looked at SEC14L2 involvement in cancer pathways through its protein network. The mRNA and protein levels of SEC14L2 are notably higher in both OSCC and HNSCC tissues compared to adjacent normal tissues. Upregulation of SEC14L2 was associated with advanced tumor stages, grades, metastasis, HPV-negative, and TP53 mutations in cancer patients. In addition, the high expression of SEC14L2 was negatively correlated with the poor survival of cancer patients and the infiltration of diverse immune cells in cancer patients. According to the findings of this investigation, SEC14L2 is significantly elevated in OSCC/HNSCC patients and associated with a worse prognosis. More investigation and clinical studies are required to completely understand the therapeutic potential of SEC14L2 in HNSCC and convert these findings into better patient outcomes.

Can Machine Learning Overcome the 95% Failure Rate and Reality that Only 30% of Approved Cancer Drugs Meaningfully Extend Patient Survival?

Despite implementing hundreds of strategies, cancer drug development suffers from a 95% failure rate over 30 years, with only 30% of approved cancer drugs extending patient survival beyond 2.5 months. Adding more criteria without eliminating nonessential ones is impractical and may fall into the "survivorship bias" trap. Machine learning (ML) models may enhance efficiency by saving time and cost. Yet, they may not improve success rate without identifying the root causes of failure. We propose a "STAR-guided ML system" (structure-tissue/cell selectivity-activity relationship) to enhance success rate and efficiency by addressing three overlooked interdependent factors: potency/specificity to the on/off-targets determining efficacy in tumors at clinical doses, on/off-target-driven tissue/cell selectivity influencing adverse effects in the normal organs at clinical doses, and optimal clinical doses balancing efficacy/safety as determined by potency/specificity and tissue/cell selectivity. STAR-guided ML models can directly predict clinical dose/efficacy/safety from five features to design/select the best drugs, enhancing success and efficiency of cancer drug development.

THOC1 complexes with SIN3A to regulate R-loops and promote glioblastoma progression

Glioblastoma (GBM), the most common and aggressive malignant brain tumor in adults, has a median survival of 21 months. To identify drivers of GBM proliferation, we conducted a CRISPR-knockout screen, which revealed THO Complex 1 (THOC1) as a key driver. Knocking down THOC1 significantly reduced GBM cell viability across patient-derived xenograft (PDX) lines, enhancing survival (p<0.01) in primary PDX models. Conversely, overexpressing THOC1 in non-cancerous cells bolstered viability, decreasing survival and causing tumor engraftment in vivo (p<0.01). Further investigation revealed THOC1's robust interaction with SIN3A, a histone deacetylase complex. Histone deacetylation has been previously shown to prevent the buildup of R-loops, structures that form normally during transcription but can be lethal in excess. We found that THOC1-knockdown leads to elevated R-loop levels and reduced histone deacetylation levels. Next, to understand the networks specifically regulated by THOC1-mediated R-loop prevention, we conducted unbiased RNA-sequencing on control and THOC1-knockdown GBM cells. We found that THOC1's role in R-loop prevention primarily affects telomeres, critical regions for cell replication. We further show that THOC1-knockdown results in significantly increased telomeric R-loop levels and shortened telomeres. Ultimately, this study suggests that targeting THOC1 shows promise as a therapeutic strategy to disrupt the delicate R-loop landscape and undermine GBM's replicative potential.

Modulation of Stemness and Differentiation Regulators by Valproic Acid in Medulloblastoma

Changes in epigenetic processes such as histone acetylation are proposed as key events influencing cancer cell function and the initiation and progression of pediatric brain tumors. Valproic acid (VPA) is an antiepileptic drug that acts partially by inhibiting histone deacetylases (HDACs) and could be repurposed as an epigenetic anticancer therapy. Here, we show that VPA reduced medulloblastoma (MB) cell viability and led to cell cycle arrest. These effects were accompanied by enhanced H3K9 histone acetylation (H3K9ac) and decreased expression of the MYC oncogene. VPA impaired the expansion of MB neurospheres enriched in stemness markers, and reduced MYC while increasing TP53 expression in these spheres. In addition, VPA induced morphological changes consistent with neuronal differentiation and increased expression of differentiation marker genes TUBB3 and ENO2 . Expression of stemness genes SOX2 , NES , and PRTG was differentially affected by VPA in MB cells with different TP53 status. VPA increased H3K9 occupancy of the promoter region of TP53 . Among genes regulated by VPA, stemness regulators MYC and NES showed association with patient survival in specific MB subgroups. Our results indicate that VPA may exert antitumor effects in MB by influencing histone acetylation, which may result in modulation of stemness, neuronal differentiation, and expression of genes associated with patient prognosis in specific molecular subgroups. Importantly, the actions of VPA in MB cells and neurospheres include a reduction in expression of MYC and increase in TP53 .

Cell-specific models reveal conformation-specific RAF inhibitor combinations that synergistically inhibit ERK signaling in pancreatic cancer cells

Pancreatic ductal adenocarcinoma (PDAC) presents significant challenges for targeted clinical interventions due to prevalent KRAS mutations, rendering PDAC resistant to RAF and MEK inhibitors (RAFi and MEKi). In addition, responses to targeted therapies vary between patients. Here, we explored the differential sensitivities of PDAC cell lines to RAFi and MEKi and developed an isogenic pair comprising the most sensitive and resistant PDAC cells. To simulate patient- or tumor-specific variations, we constructed cell-line-specific mechanistic models based on protein expression profiling and differential properties of KRAS mutants. These models predicted synergy between two RAFi with different conformation specificity (type I½ and type II RAFi) in inhibiting phospho-ERK (ppERK) and reducing PDAC cell viability. This synergy was experimentally validated across all four studied PDAC cell lines. Our findings underscore the need for combination approaches to inhibit the ERK pathway in PDAC.

Defining the heterogeneous molecular landscape of lung cancer cell responses to epigenetic inhibition

Epigenetic inhibitors exhibit powerful antiproliferative and anticancer activities. However, cellular responses to small-molecule epigenetic inhibition are heterogenous and dependent on factors such as the genetic background, metabolic state, and on-/off-target engagement of individual small-molecule compounds. The molecular study of the extent of this heterogeneity often measures changes in a single cell line or using a small number of compounds. To more comprehensively profile the effects of small-molecule perturbations and their influence on these heterogeneous cellular responses, we present a molecular resource based on the quantification of chromatin, proteome, and transcriptome remodeling due to histone deacetylase inhibitors (HDACi) in non-isogenic cell lines. Through quantitative molecular profiling of 10,621 proteins, these data reveal coordinated molecular remodeling of HDACi treated cancer cells. HDACi-regulated proteins differ greatly across cell lines with consistent (JUN, MAP2K3, CDKN1A) and divergent (CCND3, ASF1B, BRD7) cell-state effectors. Together these data provide valuable insight into cell-type driven and heterogeneous responses that must be taken into consideration when monitoring molecular perturbations in culture models.

Fibroblasts Regulate the Transformation Potential of Human Papillomavirus-positive Keratinocytes

Persistent human papillomavirus (HPV) infection is necessary but insufficient for viral oncogenesis. Additional contributing co-factors, such as immune evasion and viral integration have been implicated in HPV-induced cancer progression. It is widely accepted that HPV+ keratinocytes require co-culture with fibroblasts to maintain viral episome expression, yet the exact mechanisms for this have yet to be elucidated. Here we present comprehensive RNA sequencing and proteomic analysis demonstrating that fibroblasts not only support the viral life cycle, but reduce HPV+ keratinocyte transformation. Our co-culture models offer novel insights into HPV-related transformation mechanisms.

Genome-scale models in human metabologenomics

Metabologenomics integrates metabolomics with other omics data types to comprehensively study the genetic and environmental factors that influence metabolism. These multi-omics data can be incorporated into genome-scale metabolic models (GEMs), which are highly curated knowledge bases that explicitly account for genes, transcripts, proteins and metabolites. By including all known biochemical reactions catalysed by enzymes and transporters encoded in the human genome, GEMs analyse and predict the behaviour of complex metabolic networks. Continued advancements to the scale and scope of GEMs - from cells and tissues to microbiomes and the whole body - have helped to design effective treatments and develop better diagnostic tools for metabolic diseases. Furthermore, increasing amounts of multi-omics data are incorporated into GEMs to better identify the underlying mechanisms, biomarkers and potential drug targets of metabolic diseases.

Cancer-associated fibroblast activation predicts progression, metastasis, and prognosis of cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma (cSCC) is the most common metastatic skin cancer and the metastatic disease is associated with poor prognosis. Cancer-associated fibroblasts (CAFs) promote progression of cancer, but their role in cSCC is largely unknown. We examined the potential of CAF markers in the assessment of metastasis risk and prognosis of primary cSCC. We utilized multiplexed fluorescence immunohistochemistry for profiling CAF landscape in metastatic and non-metastatic primary human cSCCs, in metastases, and in premalignant epidermal lesions. Quantitative high-resolution image analysis was performed with two separate panels of antibodies for CAF markers and results were correlated with clinical and histopathological parameters including disease-specific mortality. Increased stromal expression of fibroblast activation protein (FAP), α-smooth muscle actin, and secreted protein acidic and rich in cysteine (SPARC) were associated with progression to invasive cSCC. Elevation of FAP and platelet-derived growth factor receptor-β (PDGFRβ) expression was associated with metastasis risk of primary cSCCs. High expression of PDGFRβ and periostin correlated with poor prognosis. Multimarker combination defined CAF subset, PDGFRα-/PDGFRβ+/FAP+, was associated with invasion and metastasis, and independently predicted poor disease-specific survival. These results identify high PDGFRβ expression alone and multimarker combination PDGFRα-/PDGFRβ+/FAP+ by CAFs as potential biomarkers for risk of metastasis and poor prognosis.

An anti-neoplastic tale of metformin through its transport

Metformin is an attractive candidate drug among all the repurposed drugs for cancer. Extensive preclinical and clinical research has evaluated its efficacy in cancer therapy, revealing a mixed outcome in clinical settings. To fully exploit metformin's therapeutic potential, understanding cellular factors relevant to its transport and accumulation in cancer cells needs to be understood. This review highlights the relevance of metformin transporter status towards its anti-cancer potential. Metformin transporters are regulated at pre-transcriptional, transcriptional, and post-translational levels. Moreover, the tumour microenvironment can also influence metformin accumulation in cancer cells. Also, Metformin treatment can regulate its transporters by altering global DNA methylation, protein acetylation, and transcription factors. Importantly, metformin transporters not only influence chemotherapeutic drug toxicity but are also associated with the prognosis and survival of individuals having cancer. Strategic decisions based on the expression and regulation of metformin transporters holds promise for its therapeutic implications and relevance.

HYENA detects oncogenes activated by distal enhancers in cancer

Somatic structural variations (SVs) in cancer can shuffle DNA content in the genome, relocate regulatory elements, and alter genome organization. Enhancer hijacking occurs when SVs relocate distal enhancers to activate proto-oncogenes. However, most enhancer hijacking studies have only focused on protein-coding genes. Here, we develop a computational algorithm 'HYENA' to identify candidate oncogenes (both protein-coding and non-coding) activated by enhancer hijacking based on tumor whole-genome and transcriptome sequencing data. HYENA detects genes whose elevated expression is associated with somatic SVs by using a rank-based regression model. We systematically analyze 1146 tumors across 25 types of adult tumors and identify a total of 108 candidate oncogenes including many non-coding genes. A long non-coding RNA TOB1-AS1 is activated by various types of SVs in 10% of pancreatic cancers through altered 3-dimensional genome structure. We find that high expression of TOB1-AS1 can promote cell invasion and metastasis. Our study highlights the contribution of genetic alterations in non-coding regions to tumorigenesis and tumor progression.

Angiotensin receptor blocker attacks armored and cold tumors and boosts immune checkpoint blockade

BACKGROUND

Immune checkpoint blockade (ICB) has made remarkable achievements, but newly identified armored and cold tumors cannot respond to ICB therapy. The high prevalence of concomitant medications has huge impact on immunotherapeutic responses, but the clinical effects on the therapeutic outcome of armored and cold tumors are still unclear.

METHODS

In this research, using large-scale transcriptomics datasets, the expression and potential biological functions of angiotensin II receptor 1 (AGTR1), the target of angiotensin receptor blocker (ARB), were investigated. Next, the roles of ARB in tumor cells and tumor microenvironment cells were defined by a series of in vitro and in vivo assays. In addition, the clinical impacts of ARB on ICB therapy were assessed by multicenter cohorts and meta-analysis.

RESULTS

AGTR1 was overexpressed in armored and cold tumors and associated with poor response to ICB therapy. ARB, the inhibitor for AGTR1, only suppressed the aggressiveness of tumor cells with high AGTR1 expression, which accounted for a very small proportion. Further analysis revealed that AGTR1 was always highly expressed in cancer-associated fibroblasts (CAFs) and ARB inhibited type I collagen expression in CAFs by suppressing the RhoA-YAP axis. Moreover, ARB could also drastically reverse the phenotype of armored and cold to soft and hot in vivo, leading to a higher response to ICB therapy. In addition, both our in-house cohorts and meta-analysis further supported the idea that ARB can significantly enhance ICB efficacy.

CONCLUSION

Overall, we identify AGTR1 as a novel target in armored and cold tumors and demonstrate the improved therapeutic efficacy of ICB in combination with ARB. These findings could provide novel clinical insight into how to treat patients with refractory armored and cold tumors.

Transcriptome- and proteome-wide association studies identify genes associated with renal cell carcinoma

We performed a series of integrative analyses including transcriptome-wide association studies (TWASs) and proteome-wide association studies (PWASs) of renal cell carcinoma (RCC) to nominate and prioritize molecular targets for laboratory investigation. On the basis of a genome-wide association study (GWAS) of 29,020 affected individuals and 835,670 control individuals and prediction models trained in transcriptomic reference models, our TWAS across four kidney transcriptomes (GTEx kidney cortex, kidney tubules, TCGA-KIRC [The Cancer Genome Atlas kidney renal clear-cell carcinoma], and TCGA-KIRP [TCGA kidney renal papillary cell carcinoma]) identified 38 gene associations (false-discovery rate <5%) in at least two of four transcriptomic panels and identified 12 genes that were independent of GWAS susceptibility regions. Analyses combining TWAS associations across 48 tissues from GTEx identified associations that were replicable in tumor transcriptomes for 23 additional genes. Analyses by the two major histologic types (clear-cell RCC and papillary RCC) revealed subtype-specific associations, although at least three gene associations were common to both subtypes. PWAS identified 13 associated proteins, all mapping to GWAS-significant loci. TWAS-identified genes were enriched for active enhancer or promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines. Using gene expression correlation, common cancers (breast and prostate) and RCC risk factors (e.g., hypertension and BMI) display genetic contributions shared with RCC. Our work identifies potential molecular targets for RCC susceptibility for downstream functional investigation.

Small-molecule GSDMD agonism in tumors stimulates antitumor immunity without toxicity

Gasdermin-mediated inflammatory cell death (pyroptosis) can activate protective immunity in immunologically cold tumors. Here, we performed a high-throughput screen for compounds that could activate gasdermin D (GSDMD), which is expressed widely in tumors. We identified 6,7-dichloro-2-methylsulfonyl-3-N-tert-butylaminoquinoxaline (DMB) as a direct and selective GSDMD agonist that activates GSDMD pore formation and pyroptosis without cleaving GSDMD. In mouse tumor models, pulsed and low-level pyroptosis induced by DMB suppresses tumor growth without harming GSDMD-expressing immune cells. Protection is immune-mediated and abrogated in mice lacking lymphocytes. Vaccination with DMB-treated cancer cells protects mice from secondary tumor challenge, indicating that immunogenic cell death is induced. DMB treatment synergizes with anti-PD-1. DMB treatment does not alter circulating proinflammatory cytokine or leukocyte numbers or cause weight loss. Thus, our studies reveal a strategy that relies on a low level of tumor cell pyroptosis to induce antitumor immunity and raise the possibility of exploiting pyroptosis without causing overt toxicity.

Circulating tumor cells: from new biological insights to clinical practice

The primary reason for high mortality rates among cancer patients is metastasis, where tumor cells migrate through the bloodstream from the original site to other parts of the body. Recent advancements in technology have significantly enhanced our comprehension of the mechanisms behind the bloodborne spread of circulating tumor cells (CTCs). One critical process, DNA methylation, regulates gene expression and chromosome stability, thus maintaining dynamic equilibrium in the body. Global hypomethylation and locus-specific hypermethylation are examples of changes in DNA methylation patterns that are pivotal to carcinogenesis. This comprehensive review first provides an overview of the various processes that contribute to the formation of CTCs, including epithelial-mesenchymal transition (EMT), immune surveillance, and colonization. We then conduct an in-depth analysis of how modifications in DNA methylation within CTCs impact each of these critical stages during CTC dissemination. Furthermore, we explored potential clinical implications of changes in DNA methylation in CTCs for patients with cancer. By understanding these epigenetic modifications, we can gain insights into the metastatic process and identify new biomarkers for early detection, prognosis, and targeted therapies. This review aims to bridge the gap between basic research and clinical application, highlighting the significance of DNA methylation in the context of cancer metastasis and offering new avenues for improving patient outcomes.

Inhibition of ADAM17 increases the cytotoxic effect of cisplatin in cervical spheroids and organoids

Introduction

Cervical cancer represents one of the main causes of female, cancer-related mortality worldwide. The majority of cancers are caused by human papillomaviruses such as HPV16 and HPV18. As chemotherapeutic resistance to first-line platinum treatment is still a predominant clinical challenge in advanced cervical cancer, novel treatment options including combinatorial therapies are urgently required to overcome chemotherapeutic resistance. Inhibition of A Disintegrin And Metalloproteinase (ADAM)-family members, heavily involved in tumour progression of a vast range of solid tumours, strongly improved response to chemotherapeutic treatment in other tumour entities including ovarian cancer.

Methods

We established two- and three-dimensional models derived from three traditional cervical cancer cell lines and ectocervical cancer-derived organoids. Following characterisation, these models were used to investigate their response to cisplatin treatment in the absence and presence of ADAM inhibitors using viability assays and automated live cell imaging.

Results

The pivotal role of the metalloprotease ADAM17 driving chemotherapy resistance was detectable in all ectocervical cultures irrespective of the model system used, whereas ADAM10 inhibition was predominantly effective only in loosely aggregated spheroids. We showed prominent differences regarding treatment responses between 2D monolayers compared to 3D spheroid and 3D organoid model systems. Particularly, the organoid system, regarded as the closest representation of primary tumours, exhibited reliably the combinatorial effect of ADAM17 inhibition and cisplatin in all three individual donors.

Discussion

As two- and three-dimensional models of the same cell lines differ in their responses to chemotherapy it is essential to validate treatment strategies in more advanced model systems representing the patient situation more realistically. Ectocervical organoids showed reliable results regarding treatment responses closely mimicking the primary tumours and could therefore serve as an important tool for personalized medicine in cervical cancer. These findings strengthen the role of ADAM17 as a potential novel target for combinatorial treatments to overcome chemoresistance in cervical cancer.

Aberrant expression of VASP serves as a potential prognostic biomarker and therapeutic target for oral squamous cell carcinoma

OBJECTIVE

To address the molecular markers linked to the development and progression of oral squamous cell carcinoma (OSCC), we sought to analyze the expression of vasodilator-stimulated phosphoproteins (VASP) in OSCC samples.

STUDY DESIGN

This study used 51 OSCC patients and The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma (TCGA-HNSC) dataset to analyze VASP expression. The association between VASP mRNA expression and HNSCC clinicopathological features, tumor infiltration, functional roles, and gene co-expression of VASP also were evaluated.

RESULTS

Our study observed increased VASP mRNA expression in OSCC tumor tissues compared to normal tissues, supported by TCGA-HNSC dataset analysis. Elevated VASP levels correlated with advanced tumor stage, higher grade, nodal metastasis, and poor survival, indicating its potential as a prognostic marker. Protein analysis and immunohistochemistry confirmed these findings, and in silico analysis revealed VASP involvement in key cancer-related processes and its correlation with IL8, RAP1A expression, and tumor infiltration levels.

CONCLUSIONS

In conclusion, VASP emerges as a promising diagnostic and prognostic marker for OSCC within HNSCC, emphasizing the importance of exploring its regulatory mechanisms and therapeutic applications. The revealed pathways present avenues for targeted treatment in OSCC. Despite limitations, this study provides valuable insights with potential implications for improving patient outcomes.

Prognostic importance of splicing-triggered aberrations of protein complex interfaces in cancer

Aberrant alternative splicing (AS) is a prominent hallmark of cancer. AS can perturb protein-protein interactions (PPIs) by adding or removing interface regions encoded by individual exons. Identifying prognostic exon-exon interactions (EEIs) from PPI interfaces can help discover AS-affected cancer-driving PPIs that can serve as potential drug targets. Here, we assessed the prognostic significance of EEIs across 15 cancer types by integrating RNA-seq data with three-dimensional (3D) structures of protein complexes. By analyzing the resulting EEI network we identified patient-specific perturbed EEIs (i.e., EEIs present in healthy samples but absent from the paired cancer samples or vice versa) that were significantly associated with survival. We provide the first evidence that EEIs can be used as prognostic biomarkers for cancer patient survival. Our findings provide mechanistic insights into AS-affected PPI interfaces. Given the ongoing expansion of available RNA-seq data and the number of 3D structurally-resolved (or confidently predicted) protein complexes, our computational framework will help accelerate the discovery of clinically important cancer-promoting AS events.

DYNC1I1 acts as a promising prognostic biomarker and is correlated with immune infiltration in head and neck squamous cell carcinoma

BACKGROUND/PURPOSE

Dynein Cytoplasmic 1 Intermediate Chain 1 (DYNC1I1) is a crucial cytoplasmic dynein binding component, its high expression levels are associated with malignant progression and poor survival in different types of cancer; however, the oncogenic role of DYNC1I1 in Head and neck squamous cell carcinomas (HNSCC) remains to be elucidated. In our present study, we aimed to explore the potential role of DYNC1I1 expression in the tumorigenesis of HNSCC and the shaping of the immune microenvironment.

MATERIALS AND METHODS

The expression levels of DYNC1I1 were analyzed in The Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) dataset, and then real-time quantitative polymerase chain reaction (RT-qPCR) was used to validate the DYNC1I1 expression in oral squamous cell carcinoma (OSCC) tumor samples, one of the major types of HNSCC. The functional pathway, tumor immune infiltration, and gene expression correlation for DYNC1I1 were performed using different bioinformatic tools.

RESULTS

We found that the expression of DYNC1I1 was significantly increased in HNSCC and was a predictor of poor survival. The DYNC1I1 high expression has also been associated with an increased risk of HPV-negative HNSCC and decreased immune cell infiltration. Functional enrichment analysis identified that DYNC1I1 is involved in several important signaling pathways that contribute to the cancer cell's survival and proliferation.

CONCLUSION

Our findings indicate that DYNC1I1 plays an important role in the tumorigenesis of HNSCC, and could be a promising prognostic biomarker for HNSCC diagnosis and treatment.

ZBTB46 coordinates angiogenesis and immunity to control tumor outcome

Tumor angiogenesis and immunity show an inverse correlation in cancer progression and outcome1. Here, we report that ZBTB46, a repressive transcription factor and a widely accepted marker for classical dendritic cells (DCs)2,3, controls both tumor angiogenesis and immunity. Zbtb46 was downregulated in both DCs and endothelial cells by tumor-derived factors to facilitate robust tumor growth. Zbtb46 downregulation led to a hallmark pro-tumor microenvironment (TME), including dysfunctional vasculature and immunosuppressive conditions. Analysis of human cancer data revealed a similar association of low ZBTB46 expression with an immunosuppressive TME and a worse prognosis. In contrast, enforced Zbtb46 expression led to TME changes to restrict tumor growth. Mechanistically, Zbtb46-deficient endothelial cells were highly angiogenic, and Zbtb46-deficient bone marrow progenitors upregulated Cebpb and diverted the DC program to immunosuppressive myeloid lineage output, potentially explaining the myeloid lineage skewing phenomenon in cancer4. Conversely, enforced Zbtb46 expression normalized tumor vessels and, by suppressing Cebpb, skewed bone marrow precursors toward immunostimulatory myeloid lineage output, leading to an immune-hot TME. Remarkably, Zbtb46 mRNA treatment synergized with anti-PD1 immunotherapy to improve tumor management in preclinical models. These findings identify ZBTB46 as a critical factor for angiogenesis and for myeloid lineage skewing in cancer and suggest that maintaining its expression could have therapeutic benefits.

Gene expression networks in endothelial cells from failing human hearts

Chronic heart failure is associated with adverse remodeling of the heart that is typically characterized by cardiomyocyte hypertrophy. This requires the formation of new capillaries to maintain oxygen supply. Insufficient angiogenesis promotes the transition from compensated hypertrophy into heart failure. The aim of this study was to identify angiogenesis-related gene networks and corresponding regulatory hubs in endothelial cells from failing human hearts. We isolated left ventricular endothelial cells from patients with advanced heart failure undergoing left ventricular assist device surgery (n = 15) and healthy organ donors (n = 2) and performed RNA sequencing. Subgroup analysis revealed no impact of comorbidities on gene expression. In a weighted gene coexpression network analysis, we found 26 gene clusters, of which 9 clusters showed a significant positive or negative correlation with the presence of heart failure. We identified the transcription factors CASZ1 (castor zinc finger 1), ZNF523 (zinc finger protein 523), and NFE2L1 (nuclear factor erythroid 2-related factor 1) as hub genes of a cluster related to angiogenesis. Knockdown of CASZ1, ZNF523, or NFE2L1 in human umbilical vein endothelial cells led to a downregulation of genes from the respective cluster, including CD34 and platelet-derived growth factor-β, confirming their regulatory function. In conclusion, we assessed gene networks in endothelial cells and identified transcription factors CASZ1, ZNF532, and NFE2L1 as potential regulators of angiogenesis in failing human hearts. Our study provides insights into the transcriptional regulation of angiogenesis beyond the classical vascular endothelial growth factor signaling pathway.NEW & NOTEWORTHY Gene coexpression network analysis defined 26 gene clusters expressed in endothelial cells from failing human hearts. Transcription factors CASZ1, ZNF523, and NFE2L1 were identified as hub genes of a cluster related to angiogenesis. Knockdown of CASZ1, ZNF523, or NFE2L1 in human umbilical vein endothelial cells led to a downregulation of genes from the respective cluster, confirming their regulatory function. This provides insights into the transcriptional regulation of angiogenesis in heart failure beyond classical signaling pathways.

Prostate cancer cancer-associated fibroblasts with stable markers post-androgen deprivation therapy associated with tumor progression and castration resistant prostate cancer

The specificity and clinical relevance of cancer-associated fibroblasts (CAFs) in prostate cancer (PCa), as well as the effect of androgen deprivation therapy (ADT) on CAFs, remain to be fully elucidated. Using cell lineage diversity and weighted gene co-expression network analysis (WGCNA), we pinpointed a unique CAF signature exclusive to PCa. The specificity of this CAF signature was validated through single-cell RNA sequencing (scRNA-seq), cell line RNA sequencing, and immunohistochemistry. This signature associates CAFs with tumor progression, elevated Gleason scores, and the emergence of castration resistant prostate cancer (CRPC). Using scRNA-seq on collected samples, we demonstrated that the CAF-specific signature is not altered by ADT, maintaining its peak signal output. Identifying a PCa-specific CAF signature and observing signaling changes in CAFs after ADT lay essential groundwork for further PCa studies.

LRRK2 G2019S enhances immune response pathways and aggravates asthma in mouse models

Asthma is a complex inflammatory airway disease that arises from the interplay between genetic predisposition and environmental influences. Leucine-rich repeat kinase 2 (LRRK2), a gene commonly associated with Parkinson's disease, has recently gained attention for its role in immune regulation and inflammation beyond the brain. However, its involvement in asthma has not yet been reported. In this study, we used LRRK2 G2019S transgenic mice and LRRK2 knockout mice to establish asthmatic models to explore LRRK2 impact on asthma. We found that LRRK2 G2019S transgenic mice showed exacerbated airway hyperresponsiveness (AHR) and airway inflammation in asthma mouse models induced by house dust mite. RNA sequencing data unveiled that the LRRK2 G2019S mutation enhanced immune response pathways, including NOD-like receptor, cellular response to interferon β and activation of innate immune response signaling. Conversely, LRRK2 deficiency attenuated AHR and airway inflammation in the same asthma models. Our study offers new insights into the role of LRRK2 in allergic inflammation and highlights its potential as a therapeutic target for asthma.

Vasculogenic mimicry-related gene prognostic index for predicting prognosis, immune microenvironment in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a highly aggressive cancer associated with higher death rates. However, traditional anti-angiogenic therapies have limited effectiveness due to drug resistance. Vascular mimicry (VM) provides a different way for tumors to develop blood vessels without relying on endothelial cells or angiogenesis. However, the intricate mechanisms and interplay between it and the immune microenvironment in ccRCC remain unclear.

Methods

A PubMed and GeneCards literature review was conducted to identify VM-related genes (VMRGs). VMRGs expression profiles were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), developing a novel VM risk score model and nomogram for ccRCC. The EBI ArrayExpress database (the validation set) was obtained to validate the prognostic model. The relationship between VMRGs risk score clinical characteristics and immune infiltration was investigated. Finally, the expression of six model VMRGs was validated using single-cell analysis, GEPIA, Human Protein Atlas (HPA), and quantitative Real-time PCR (qRT-PCR).

Results

Cox regression analysis and nomogram identified L1CAM, TEK, CLDN4, EFNA1, SERPINF1, and MALAT1 as independent prognostic risk factors, which could be used to stratify the ccRCC population into two risk groups with distinct immune profiles and responsiveness to immunotherapy. The results of single-cell analysis, GEPIA, HPA, and qRT-PCR validated the model genes' expression.

Conclusions

Our novel findings constructed a convenient and reliable 6 gene signatures as potential immunologic and prognostic biomarkers of VM in ccRCC.

Unveiling the Therapeutic Potential of Folate-Dependent One-Carbon Metabolism in Cancer and Neurodegeneration

Cellular metabolism is crucial for various physiological processes, with folate-dependent one-carbon (1C) metabolism playing a pivotal role. Folate, a B vitamin, is a key cofactor in this pathway, supporting DNA synthesis, methylation processes, and antioxidant defenses. In dividing cells, folate facilitates nucleotide biosynthesis, ensuring genomic stability and preventing carcinogenesis. Additionally, in neurodevelopment, folate is essential for neural tube closure and central nervous system formation. Thus, dysregulation of folate metabolism can contribute to pathologies such as cancer, severe birth defects, and neurodegenerative diseases. Epidemiological evidence highlights folate's impact on disease risk and its potential as a therapeutic target. In cancer, antifolate drugs that inhibit key enzymes of folate-dependent 1C metabolism and strategies targeting folate receptors are current therapeutic options. However, folate's impact on cancer risk is complex, varying among cancer types and dietary contexts. In neurodegenerative conditions, including Alzheimer's and Parkinson's diseases, folate deficiency exacerbates cognitive decline through elevated homocysteine levels, contributing to neuronal damage. Clinical trials of folic acid supplementation show mixed outcomes, underscoring the complexities of its neuroprotective effects. This review integrates current knowledge on folate metabolism in cancer and neurodegeneration, exploring molecular mechanisms, clinical implications, and therapeutic strategies, which can provide crucial information for advancing treatments.

Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses

The druggable proteome refers to proteins that can bind to small molecules with appropriate chemical affinity, inducing a favorable clinical response. Predicting druggable proteins through screening and in silico modeling is imperative for drug design. To contribute to this field, we developed an accurate predictive classifier for druggable cancer-driving proteins using amino acid composition descriptors of protein sequences and 13 machine learning linear and non-linear classifiers. The optimal classifier was achieved with the support vector machine method, utilizing 200 tri-amino acid composition descriptors. The high performance of the model is evident from an area under the receiver operating characteristics (AUROC) of 0.975 ± 0.003 and an accuracy of 0.929 ± 0.006 (threefold cross-validation). The machine learning prediction model was enhanced with multi-omics approaches, including the target-disease evidence score, the shortest pathways to cancer hallmarks, structure-based ligandability assessment, unfavorable prognostic protein analysis, and the oncogenic variome. Additionally, we performed a drug repurposing analysis to identify drugs with the highest affinity capable of targeting the best predicted proteins. As a result, we identified 79 key druggable cancer-driving proteins with the highest ligandability, and 23 of them demonstrated unfavorable prognostic significance across 16 TCGA PanCancer types: CDKN2A, BCL10, ACVR1, CASP8, JAG1, TSC1, NBN, PREX2, PPP2R1A, DNM2, VAV1, ASXL1, TPR, HRAS, BUB1B, ATG7, MARK3, SETD2, CCNE1, MUTYH, CDKN2C, RB1, and SMARCA4. Moreover, we prioritized 11 clinically relevant drugs targeting these proteins. This strategy effectively predicts and prioritizes biomarkers, therapeutic targets, and drugs for in-depth studies in clinical trials. Scripts are available at https://github.com/muntisa/machine-learning-for-druggable-proteins .

FAM122A functions as a tumor suppressor in oral squamous cell carcinoma

Family with sequence similarity 122a (FAM122A), identified as an endogenous inhibitor of protein phosphatase 2A (PP2A) previously, is involved in multiple important physiological processes, and essential for the growth of acute myeloid leukemia and hepatocellular carcinoma cells. However, the function of FAM122A in oral squamous cell carcinoma (OSCC) is undetermined. In this study, by analyzing TCGA and GEO databases, we found that the expression of FAM122A was significantly down-regulated in head and neck squamous cell carcinoma and OSCC patients, meanwhile this low expression was tightly associated with the poor prognosis and advanced clinical stage during OSCC development. The similar low expression pattern of FAM122A could also been seen in OSCC cell lines compared with normal human oral keratinocytes. Further, we demonstrated that FAM122A knockdown significantly promoted the growth, clonogenic potential as well as migration capabilities of OSCC cells, while these alterations could be rescued by the re-expression of FAM122A. Over-expression of FAM122A suppressed OSCC cell proliferation and migration. FAM122A also inhibited the epithelial-mesenchymal transition (EMT) in OSCC cells by the up-regulation of epithelial marker E-cadherin and down-regulation of mesenchymal markers Fibronectin and Vimentin, which is presumably mediated by transforming growth factor β receptor 3 (TGFBR3), a novel tumor suppressor. In addition, FAM122A could induce T cell infiltration in OSCC, indicating that FAM122A might influence the immune cell activity of tumor environment and further interfere the tumor development. Collectively, our results suggest that FAM122A functions as a tumor suppressor in OSCC and possibly acts as a predictive biomarker for the diagnosis and/or treatment of OSCC.

Comprehensive genomic profiling of infiltrative follicular variant of papillary thyroid carcinoma

BACKGROUND

Infiltrative follicular variant of papillary thyroid carcinoma (IFVPTC) exhibits nuclear characteristics typical of papillary thyroid carcinoma (PTC) but demonstrates a follicular growth pattern. The diagnosis of IFVPTC presenting with atypical nuclear features of PTC poses challenges for both preoperative cytopathology and postoperative histopathology. In such cases, molecular markers are needed to serve as diagnostic aids. Given the limited knowledge of IFVPTC's genomic features, this study aimed to characterize its genetic alterations and identify clinically relevant molecular markers.

METHODS

Whole-exome sequencing of 50 IFVPTC tumor-normal pairs identified single-nucleotide variants, somatic copy number alterations (sCNAs), and subclonal architecture. Key mutations were verified via polymerase chain reaction and Sanger sequencing, whereas valuable biomarkers were validated via immunohistochemistry (IHC).

RESULTS

This study found that endogenous processes rather than exogenous mutagens dominated the shaping of the genome of IFVPTC during tumorigenesis. BRAF V600E was the only common trunk mutation and significantly mutated gene in IFVPTC. Subcloning analysis found that most IFVPTC samples harbored two or more coexisting clones. sCNA analysis revealed that human leukocyte antigen C (HLA-C) and HLA-A were significantly amplified. Subsequent IHC investigations indicated that HLA-C shows promise in averting the misclassification of challenging-to-interpret IFVPTC and invasive encapsulated follicular variant of PTC (I-EFVPTC) as noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Although there were several similarities between classic PTC and IFVPTC, they differed significantly in their sCNA patterns.

CONCLUSIONS

This study provides valuable insights into IFVPTC's genetic alterations and highlights the potential of HLA-C IHC to distinguish challenging-to-interpret IFVPTC and I-EFVPTC from NIFTP, which will enhance the understanding of its molecular features for improved diagnosis and management.

Activation of the TRPML1 Ion Channel Induces Proton Secretion in the Human Gastric Parietal Cell Line HGT-1

The lysosomal Ca2+ channel TRPML1 was found to be responsible for gastric acid secretion in murine gastric parietal cells by inducing the trafficking of H+/K+-ATPase containing tubulovesicles to the apical membrane. Therefore, we hypothesized a similar role of TRPML1 in regulating proton secretion in the immortalized human parietal cell line HGT-1. The primary focus was to investigate the involvement of TRPML1 in proton secretion using the known synthetic agonists ML-SA1 and ML-SA5 and the antagonist ML-SI3 and, furthermore, to identify food-derived compounds that target the channel. Proton secretion stimulated by ML-SA1 was reduced by 122.2 ± 22.7% by the antagonist ML-SI3. The steroid hormone 17β-estradiol, present in animal-derived foods, diminished the proton secretory effect of ML-SA1 by 63.4 ± 14.5%. We also demonstrated a reduction in the proton secretory effects of ML-SA1 and ML-SA5 on TRPML1 knock-down cells. The food-derived compounds sulforaphane and trehalose promoted proton secretion in HGT-1 cells but may act independently of TRPML1. Also, histamine- and caffeine-induced proton secretion were affected by neither the TRPML1 antagonist ML-SI3 nor the TRPML1 knock-down. In summary, the results obtained suggest that the activation of TRPML1 promotes proton secretion in HGT-1 cells, but the channel may not participate in canonical signaling pathways.

PLEK2 promotes migration and invasion in pancreatic ductal adenocarcinoma by MMP1 through IL-17 pathway

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor prognosis primarily due to metastasis. Accumulating evidence suggests that PLEK2 acts as an oncogene in various tumors. This study aimed to investigate the effects of PLEK2 on PDAC. Expression analysis of PLEK2 was conducted using qRT-PCR, Western blot, and immunohistochemistry in PDAC. Wound healing and transwell assays were performed to evaluate the impact of PLEK2 on cell migration and invasion. A xenograft tumor model was employed to assess the in vivo proliferation of PLEK2. Additionally, the downstream pathway of PLEK2 was analyzed through RNA-seq and confirmed by Western blot analysis. The results demonstrated the upregulation of PLEK2 expression in tumor specimens. High PLEK2 expression was significantly associated with poor overall survival and advanced TNM stages. Correlation analyses revealed positive correlations between PLEK2 and TGF-β, EGFR, and MMP1. Wound healing and transwell assays demonstrated that PLEK2 promoted PDAC cell migration and invasion, potentially through the activation of the epithelial-to-mesenchymal transition process. The in vivo experiment further confirmed that PLEK2 knockdown suppressed tumor growth. RNA-seq analysis revealed PLEK2's regulation of MMP1 and activation of p-ERK and p-STAT3, which were verified by Western blot analysis. Overall, the present study suggests that PLEK2 may play a tumor-promoting role in PDAC. These findings provide valuable insights into the molecular mechanisms of pancreatic cancer and highlight the potential of PLEK2 as a therapeutic target.

Occlusion enhanced pan-cancer classification via deep learning

Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue of origin of a sample and discovering marker genes. Existing studies typically identify marker genes by statistically comparing healthy and cancer samples. However, this approach overlooks marker genes with low expression level differences and may be influenced by experimental results. This paper introduces "GENESO," a novel framework for pan-cancer classification and marker gene discovery using the occlusion method in conjunction with deep learning. we first trained a baseline deep LSTM neural network capable of distinguishing the origins and statuses of samples utilizing RNA-Seq data. Then, we propose a novel marker gene discovery method called "Symmetrical Occlusion (SO)". It collaborates with the baseline LSTM network, mimicking the "gain of function" and "loss of function" of genes to evaluate their importance in pan-cancer classification quantitatively. By identifying the genes of utmost importance, we then isolate them to train new neural networks, resulting in higher-performance LSTM models that utilize only a reduced set of highly relevant genes. The baseline neural network achieves an impressive validation accuracy of 96.59% in pan-cancer classification. With the help of SO, the accuracy of the second network reaches 98.30%, while using 67% fewer genes. Notably, our method excels in identifying marker genes that are not differentially expressed. Moreover, we assessed the feasibility of our method using single-cell RNA-Seq data, employing known marker genes as a validation test.

Comprehensive analysis, diagnosis, prognosis, and cordycepin (CD) regulations for GSDME expressions in pan-cancers

The Gasdermin E gene (GSDME) plays roles in deafness and cancers. However, the roles and mechanisms in cancers are complex, and the same gene exhibits different mechanisms and actions in different types of cancers. Online databases, such as GEPIA2, cBioPortal, and DNMIVD, were used to comprehensively analyze GSDME profiles, DNA methylations, mutations, diagnosis, and prognosis in patients with tumor tissues and matched healthy tissues. Western blotting and RT-PCR were used to monitor the regulation of GSDME by Cordycepin (CD) in cancer cell lines. We revealed that GSDME expression is significantly upregulated in eight cancers (ACC, DLBC, GBM, HNSC, LGG, PAAD, SKCM, and THYM) and significantly downregulated in seven cancers (COAD, KICH, LAML, OV, READ, UCES, and UCS). The overall survival was longer only in ACC, but shorter in four cancers, including COAD, KIRC, LIHC, and STAD, when GSDME was highly expressed in cancers compared with the corresponding normal tissues. Moreover, the high expression of GSDME was negatively correlated with the poor prognosis of ACC, while the low expression of GSDME was negatively correlated with the poor prognosis of COAD, suggesting that GSDME might serve as a good prognostic factor in these two cancer types. Accordingly, results indicated that the DNA methylations of those 7 CpG sites constitute a potentially effective signature to distinguish different tumors from adjacent healthy tissues. Gene mutations for GSDME were frequently observed in a variety of tumors, with UCES having the highest frequency. Moreover, CD treatment inhibited GSDME expression in different cancer cell lines, while overexpression of GSDME promoted cell migration and invasion. Thus, we have systematically and successfully clarified the GSDME expression profiles, diagnostic values, and prognostic values in pan-cancers. Targeting GSDME with CD implies therapeutic significance and a mechanism for antitumor roles in some types of cancers via increasing the sensitivity of chemotherapy. Altogether, our study may provide a strategy and biomarker for clinical diagnosis, prognostics, and treatment of cancers by targeting GSDME.