Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide, underscoring the urgent need for precise and personalized therapeutic strategies. Globo-H has emerged as a clinically relevant glycan target with promising diagnostic and therapeutic utility across multiple cancer types. In this study, we stratified colorectal cancer patients into Globo-H-high and Globo-H-low groups using a histology-based classification, followed by RNA-sequencing analyses to elucidate the key signaling pathways associated with Globo-H overactivation. Among the 31 genes that were identified to meet the Globo-H histology criterion, DUSP14 (dual specificity phosphatase 14) emerged as a promising pharmacological target associated with Globo-H abundance. DUSP14 is an underexplored but pharmacologically actionable therapeutic target. DUSP14 protein in colon cancer cells is inversely correlated with total Transforming growth factor-β-activated kinase 1 (TAK1) protein. The druggability of DUSP14 was demonstrated through in vitro using cell lines and patient-derived organoids (PDO). These results enhance current diagnostic frameworks and provide a foundation for developing novel targeted therapies. Further, in vivo studies are warranted to evaluate the potential of Globo-H targeting in combination with standard treatment regimens. Overall, our work highlights the value of integrating PDO-based functional assays with molecular profiling to uncover and validate actionable targets for CRC theranostics.

This study evaluates whether indocyanine green (ICG) fluorescence during hypothermic oxygenated machine perfusion (HOPE) can predict early allograft dysfunction (EAD) after liver transplantation. Seventeen donor livers underwent HOPE before transplantation. After one hour, ICG was administered via the portal line. Perfusate samples were collected every five minutes for 50 min; liver tissue and bile samples were obtained during perfusion and after reperfusion. Fluorescence intensity (FI) was quantified using standardized microplate analysis. Associations with donor characteristics and clinical outcomes were analyzed. EAD occurred in 29.4

Introduction Colorectal cancer (CRC) ranks third in men and second in women, with 153,020 new cases and 52,550 deaths in 2023, and with a projected incidence of 2.2 million new cases by 2030 due to lifestyle changes and enhanced diagnostic capabilities. Identification and analysis of new biomarkers, like lens epithelium-derived growth factor splice variant of 75 kDa (LEDGF/p75), which is known to play a crucial role as stress-related oncogene, can make a significant contribution in facilitating early CRC detection. Methods This study analyzed the expression of LEDGF/p75 and the ubiquitin E2 conjugating enzyme UBC13 in 15 CRC tissue samples and adjacent non-tumor tissues. All patient samples underwent NGS-based mutation analysis beforehand. The western blot technique was used for protein analysis, and the results were further validated using mRNA expression data from 521 patient samples from the TCGA database. Results LEDGF/p75 expression was significantly elevated in nearly all tumor tissue samples compared to adjacent tissue (11/15, 73.3%). Additionally, the UBC13 enzyme, a key regulator in the degradation of signaling molecules, was also increased in most tumor tissue samples (9/15, 60.0%). Co-overexpression of LEDGF/p75 and UBC13 was evident in 6/6 patients. Patients with KRAS and MSH2 mutations showed a 75% and 100% correlation with LEDGF/p75 overexpression, respectively. Conclusion This study confirms the upregulation of LEDGF/p75 in CRC and shows its correlation with KRAS and MSH2 mutations. The interaction of LEDGF/p75 with DNA damage response proteins may contribute to drug resistance and increased tumor aggressiveness. LEDGF/p75’s potential as a prognostic biomarker independent of lymph node involvement or CEA levels highlights its potential in personalized therapy, and warrants further research into its therapeutic targeting.

IntroductionThe OCRA Tabletop MRI System is a compact, low-field (0.24T) magnetic resonance platform originally developed as an educational device to teach MR physics using chemical test tube-sized samples. Given its capabilities, we explored its diagnostic potential by performing relaxometric analysis on freshly resected human tissue specimens.MethodsMatched pairs of histologically confirmed tumor and non-tumor samples were analyzed with the OCRA MRI system to determine T1 and T2 relaxation times via NMR spectroscopy. In parallel, mRNA expression levels of ZEB1, a key transcription factor involved in WNT signaling, stem cell maintenance and tumor-stroma interactions were quantified for each sample.ResultsThe measured T1 and T2 relaxation times showed distinct profiles between tumor and non-tumor tissues. These biophysical properties were correlated with ZEB1 mRNA expression, revealing preliminary associations between tissue relaxation behavior and molecular signatures relevant to tumor microenvironment dynamics.ConclusionAlthough this pilot study does not yet confirm clinical diagnostic utility, it offers initial biophysical insights into tumor-associated tissue alterations and provides a foundation for future validation studies in larger patient cohorts.

ABSTRACT Background Panitumumab shows limited clinical benefit in colorectal cancer (CRC), and reliable predictive biomarkers to guide patient selection remain lacking. To address this gap, we investigated molecular determinants of therapeutic response using tumor samples from patients with primary and metastatic CRC. By integrating PIMS‐based metastatic classification, NPOT interaction profiling and quantitative proteomics, this study aimed to identify response‐associated pathways and potential prognostic biomarkers that could support improved stratification for panitumumab therapy. Method Twenty‐one tumor resection samples from twenty CRC patients from primary site (n = 12) and from intrahepatic metastasis (n = 9), female (n = 6) and male (n = 14) were analyzed. Clinical metadata of donors was associated with molecular properties of each sample. Patients’ cryostored tumor material was blinded before subjecting to PIMS analysis. PIMS analysis was at first performed to separate metastatic and non‐metastatic patients. After uncovering the blind, tumors were all challenged by 1 μg of panitumumab in PIMS to identify responder and non‐responder with or without metastasis. Tumors from metastatic (n = 3) and non‐metastatic (n = 2) patients were thereafter analyzed by NPOT to identify EGFR‐related signaling pathway. All group tumors were analyzed using label‐free quantitative proteomics. Results PIMS identified with 82% accuracy metastatic (n = 9) from non‐metastatic (n = 7) tumor. The metastatic tumor had higher resonance volumes (2948–5094) compared to non‐metastatic (1076–2759) tumor. NPOT identified EGFR only in metastatic tumor. The metastatic interactome was composed of 34 proteins (EGFR, PTPN1, CTNNB1, CTNND1, YWHAZ, CD44, FN1, ITGB1, GADPH, ENO1, HSPA4, HSPA8, HSP90AA1, HSP90AB1, ANXA2, A1BG, DNTM1, TSR1, RPS27, PPM1G, SMC2, LIG1, NCAPD2, POLD1, PRKDC, YBX1, ANK1, FTL, NCL, ITGB2, SERPINA7, HP, and A2M). The first 10 proteins (underlined) were shared also with non‐metastatic tumors. Label‐free quantitative proteomics identified 145 differentiated protein, 15 of which were enriched and 130 impoverished specifically in metastatic tumors. Evidence suggests that HSPA4, HSP90AB1, DNTM1, RPS27, FTL, NCL, A2M are implicated in the pathogenesis and progression of colorectal cancer, positioning them as potential prognostic biomarkers for the onset of metastasis. Conclusion Combination of PIMS and NPOT coupled to label‐free quantitative proteomics point towards the distinct panitumumab mode of action in CRC patients and highlights specific proteins as prognostic biomarkers which need further validation in a bigger cohort and multicentric investigation, ideally involving patient registry follow up data. Novelty and Impact This study presents an integrative molecular profiling strategy that combines PIMS, NPOT, and proteomics to uncover mechanistically relevant biomarkers of therapeutic response in colorectal cancer. By identifying an EGFR‐centered interactome and responder‐specific protein signatures, the research offers a novel approach to stratify panitumumab response and supports advancement of precision oncology in clinical settings.

In recent years, more complex robotic-assisted liver resections (RLR) have been performed, providing a viable alternative to open liver resection (OLR). While the short-term benefits of minimally invasive surgery are well known, including reduced blood loss and shorter hospital stay, the inflammatory response to different surgical approaches remains poorly understood. This study examines the immune response in peripheral blood and local liver and peritoneal tissue during and after liver surgery in 22 patients (11 in each group). The study analyzes clinical and laboratory parameters, leukocyte activation, and cytokine/chemokine levels before and after liver parenchyma dissection using L-selectin shedding assay and FACS multiplex analysis panel. In the perioperative course, systemic and local liver cytokine levels of IL-6 and IL-10 are reduced in RLR. The laparotomy itself resulted in higher baseline levels of IL-6, IL-8, CXCL10, IFNγ, TGFβ1, and IL-1β in local liver tissue of the OLR group. After liver parenchyma dissection, RLR patients exhibited reduced levels of IL-6, IL-8, IFNγ, MCP1, IL-1β, TGFβ1, and CXCL10 in the liver compared to the OLR group. In the late postoperative course from postoperative day (POD) 5–20, systemic chemokine MCP1 was reduced, alongside a decrease of CD4+/CD8+ lymphocytes and higher L-selectin shedding capacity in the RLR group from POD5 onwards. These findings suggest that RLR preserves immune competence more effectively than OLR in the peri- and late postoperative course. The reduced systemic and local inflammatory response may be the result of less tissue damage with reduced cytokine release, highlighting the value of less traumatic surgery applied by robotic systems during clinical practice.

Colorectal cancer (CRC) represents the third leading cause of cancer-related deaths. Integrating cellular and molecular data from individual patients has become valuable for diagnosis, prognosis, and treatment selection. Here, we present a comparative mRNA-seq analysis of tissue samples from 32 CRC patients, pairing tumors with adjacent healthy tissues. Differential expression gene (DEG) analysis revealed dysregulated metabolic programs. We focused on the impact of overexpressed SLC7A11 (xCT) and SLC3A2, which compose the cystine/glutamate transporter (Xc-) system. To assess the oncogenic potential of the Xc- system, we analyzed gene perturbations from CRISPR screens across various cell types and used functional assays in five primary patient-derived organoid models. We identified a previously uncharacterized cell surface protein signature predicting chemotherapy resistance and highlighted the causality and potential of pharmacological blockage of ferroptosis as a promising avenue for cancer therapy. Redox homeostasis, ion/amino acid transporters, and regulators of neuronal survival and differentiation were pathways associated with these co-dependent genes in patient specimens. This study highlights several potential clinical targets for CRC therapy and promotes the use of patient-derived organoids oids to functionally validate in silico predictions.

Colorectal cancer (CRC) represents the third-leading cause of cancer-related deaths. Here, we present an in-depth comparative mRNA-seq and microRNA-seq analysis of tissue samples from 32 CRC, pairing tumors with adjacent healthy tissues. The differential expression gene (DEG) analysis revealed an interconnection between nutrients, metabolic programs, and cell cycle pathways. We focused on the impact of overexpressed SLC7A11 (xCT) and SLC3A2 genes which compose the cystine/glutamate transporter (Xc-) system. We applied a knowledge-based approach for analyzing gene perturbations from CRISPR screens across various cell types as well as using a variety of functional assays in five primary patient-derived organoid cell models to functionally verify our hypothesis. We identified a previously undescribed cell surface protein signature predicting chemotherapy resistance and further highlighted the causality and potential of pharmacological blockage of ferroptosis as promising avenue for cancer therapy. Biological processes such as redox homeostasis, ion/amino acid transporters and de novo nucleotide synthesis were associated with these co-dependent genes. This study highlighted overlooked genes as potential clinical targets with focus on SLC7A11 and its associated genes in tumorigenesis.

Background: Uncover the pivotal link between lymphocyte-specific protein tyrosine kinase (Lck)-related genes and clinical risk stratification in pancreatic cancer.Methods: This study identifies shared genes between differentially expressed genes (DEGs) and Lck-related genes in pancreatic cancer using a methodological framework rooted in The Cancer Genome Atlas database. Feature gene selection is accomplished and a signature model is constructed. Statistical significant clinical endpoints such as overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were defined.Results: After performing random survival forest, Lasso regression, and multivariate Cox regression model, 7 trait genes out of 272 Lck-associated DEGs are selected to create a signature model that is independent of other clinical factors and can predict OS and DSS. It appears that high-risk patients have activated the TP53 signaling pathway and the cell cycle signaling pathway. LAMA3 turned out to be the hub gene of the signature with high expression in pancreatic cancer. Patients with increased expression of LAMA3 had a short OS, DSS, and PFI in comparison. The candidate competing endogenous RNA network of LAMA3 turned out to be OPI5-AS1/hsa-miR-186-5p/LAMA3 axis.Conclusions: A characteristic signature of seven Lck-related genes, especially LAMA3, has been shown to be a key factor in clinical risk stratification for pancreatic cancer.

Introduction Colorectal cancer ranks third in men and second in women, with 153,020 new cases and 52,550 deaths in 2023. While predominantly affecting those over 65 years, 13% occur in individuals under 50 years. Biomarker analysis, including APC, BRAF, KRAS, and TP53, aids early detection, but rising incidence due to lifestyle changes projects 2.2 million new cases by 2030. Early screening is crucial for optimizing treatment outcomes and disease monitoring in colorectal cancer, as it enables the identification and intervention of malignancy at an early stage, thereby improving survival rates and reducing the need for invasive procedures - this process is significantly augmented by the use of early biomarkers. Methods This study analyzed the expression of the stress oncoprotein LEDGF/p75 and the ubiquitin E2 conjugating enzyme UBC13 in 15 colorectal cancer tissue samples and adjacent non-tumor tissues, obtained from the same patients. Western blot analysis was used, and results were further validated using mRNA expression data from 521 patients in the TCGA database. Results LEDGF/p75 expression was significantly elevated in nearly all tumor tissue samples compared to adjacent tissue (11 / 15, 73.3 %). Additionally, enzyme UBC13, a key regulator in the degradation of signaling molecules, was also increased in most tumor tissue samples (9 / 15, 60.0 %). Co-overexpression of LEDGF/p75 and UBC13 was evident in 6 / 6 patients. Conclusion This study confirms the upregulation of LEDGF/p75 in colorectal cancer and shows its correlation with KRAS and MSH2 mutations. The role of LEDGF/p75 in genomic instability and interactions with DNA repair proteins may contribute to drug resistance and increased tumor aggressiveness. LEDGF/p75’s potential as a prognostic biomarker independent of lymph node involvement or CEA levels highlights its potential in personalized therapy and warrants further research into its therapeutic targeting.

Colorectal cancer (CRC) represents the third leading cause of cancer-related deaths. Knowledge covering diverse cellular and molecular data from individual patients has become valuable for diagnosis, prognosis, and treatment selection. Here, we present in-depth comparative RNA-seq analysis of 32 CRC patients pairing tumor and healthy tissues (total of 73 samples). Strict thresholds for differential expression genes (DEG) analysis revealed an interconnection between nutrients, metabolic program, and cell cycle pathways. Among the upregulated DEGs, we focused on the Xc- system, composed of the proteins from SLC7A11 (xCT) and SLC3A2 genes, along with several interacting genes. To assess the oncogenic potency of the Xc- system in a cellular setting, we applied a knowledge-based approach, analyzing gene perturbations from CRISPR screens. The study focused on a set of 27 co-dependent genes that were strongly correlated with the fitness of SLC7A11 and SLC3A2 across many cell types. Alterations in these genes in 13 large-scale studies (e.g., by mutations and copy number variation) were found to enhance overall survival and progression-free survival in CRC patients. In agreement, the overexpression of these genes in cancer cells drives cancer progression by allowing effective management of the redox level, induction of stress response mechanisms, and most notably, enhanced activity of ion/amino acid transporters, and enzymes acting in de novo nucleotide synthesis. We also highlight the positive correlation between the Xc- system gene expression level, patient responsiveness to different chemotherapy treatments, and immune cell infiltration ( e.g., myeloid-derived suppressor cells) in CRC tumors as a measure for their immunosuppressive activity. This study illustrates that knowledge-based interpretation by synthesizing multiple layers of data leads to functional and mechanistic insights into the role of SLC7A11 and its associated genes in CRC tumorigenesis and therapeutics.

IntroductionPancreatic cancer is a highly aggressive cancer, and early diagnosis significantly improves patient prognosis due to the early implementation of curative-intent surgery. Our study aimed to implement machine-learning algorithms to aid in early pancreatic cancer diagnosis based on minimally invasive liquid biopsies.Materials and methodsThe analysis data were derived from nine public pancreatic cancer miRNA datasets and two sequencing datasets from 26 pancreatic cancer patients treated in our medical center, featuring small RNAseq data for patient-matched tumor and non-tumor samples and serum. Upon batch-effect removal, systematic analyses for differences between paired tissue and serum samples were performed. The robust rank aggregation (RRA) algorithm was used to reveal feature markers that were co-expressed by both sample types. The repeatability and real-world significance of the enriched markers were then determined by validating their expression in our patients' serum. The top candidate markers were used to assess the accuracy of predicting pancreatic cancer through four machine learning methods. Notably, these markers were also applied for the identification of pancreatic cancer and pancreatitis. Finally, we explored the clinical prognostic value, candidate targets and predict possible regulatory cell biology mechanisms involved.ResultsOur multicenter analysis identified hsa-miR-1246, hsa-miR-205-5p, and hsa-miR-191-5p as promising candidate serum biomarkers to identify pancreatic cancer. In the test dataset, the accuracy values of the prediction model applied via four methods were 94.4%, 84.9%, 82.3%, and 83.3%, respectively. In the real-world study, the accuracy values of this miRNA signatures were 82.3%, 83.5%, 79.0%, and 82.2. Moreover, elevated levels of these miRNAs were significant indicators of advanced disease stage and allowed the discrimination of pancreatitis from pancreatic cancer with an accuracy rate of 91.5%. Elevated expression of hsa-miR-205-5p, a previously undescribed blood marker for pancreatic cancer, is associated with negative clinical outcomes in patients.ConclusionA panel of three miRNAs was developed with satisfactory statistical and computational performance in real-world data. Circulating hsa-miRNA 205-5p serum levels serve as a minimally invasive, early detection tool for pancreatic cancer diagnosis and disease staging and might help monitor therapy success.

Patient-derived xenograft (PDX) tumor models are essential for identifying new biomarkers, signaling pathways and novel targets, to better define key factors of therapy response and resistance mechanisms. Therefore, this study aimed at establishing pancreas carcinoma (PC) PDX models with thorough molecular characterization, and the identification of signatures defining responsiveness toward drug treatment. In total, 45 PC-PDXs were generated from 120 patient tumor specimens and the identity of PDX and corresponding patient tumors was validated. The majority of engrafted PDX models represent ductal adenocarcinomas (PDAC). The PDX growth characteristics were assessed, with great variations in doubling times (4 to 32 days). The mutational analyses revealed an individual mutational profile of the PDXs, predominantly showing alterations in the genes encoding KRAS, TP53, FAT1, KMT2D, MUC4, RNF213, ATR, MUC16, GNAS, RANBP2 and CDKN2A. Sensitivity of PDX toward standard of care (SoC) drugs gemcitabine, 5-fluorouracil, oxaliplatin and abraxane, and combinations thereof, revealed PDX models with sensitivity and resistance toward these treatments. We performed correlation analyses of drug sensitivity of these PDX models and their molecular profile to identify signatures for response and resistance. This study strongly supports the importance and value of PDX models for improvement in therapies of PC.

Current treatment for glioblastoma includes tumor resection followed by radiation, chemotherapy, and periodic post-operative examinations. Despite combination therapies, patients face a poor prognosis and eventual recurrence, which often occurs at the resection site. With standard MRI imaging surveillance, histologic changes may be overlooked or misinterpreted, leading to erroneous conclusions about the course of adjuvant therapy and subsequent interventions. To address these challenges, we propose an implantable system for accurate continuous recurrence monitoring that employs optical sensing of fluorescently labeled cancer cells and is implanted in the resection cavity during the final stage of tumor resection. We demonstrate the feasibility of the sensing principle using miniaturized system components, optical tissue phantoms, and porcine brain tissue in a series of experimental trials. Subsequently, the system electronics are extended to include circuitry for wireless energy transfer and power management and verified through electromagnetic field, circuit simulations and test of an evaluation board. Finally, a holistic conceptual system design is presented and visualized. This novel approach to monitor glioblastoma patients is intended to early detect recurrent cancerous tissue and enable personalization and optimization of therapy thus potentially improving overall prognosis.

The proportion of patients diagnosed with cancer has been shown to rise with the increasing aging global population. Advanced age is a major risk factor for morbidity and mortality in older adults. As individuals experience varying health statuses, particularly with age, it poses a challenge for medical professionals in the cancer field to obtain standardized treatment outcomes. Hence, relying solely on chronological age and disease-related parameters is inadequate for clinical decision-making for elderly patients. With functional, multimorbidity-related, and psychosocial changes that occur with aging, oncologic diseases may develop and be treated differently from younger patients, leading to unique challenges in treatment efficacy and tolerance. To overcome this challenge, personalized therapy using biomarkers has emerged as a promising solution. Various categories of biomarkers, including inflammatory, hematological, metabolic, endocrine, and DNA modification-related indicators, may display features related to both cancer and aging, aiding in the development of innovative therapeutic approaches for patients with cancer in old age. Furthermore, physical functional measurements as non-molecular phenotypic biomarkers are being investigated for their potential complementary role in structured multidomain strategies to combat age-related diseases such as cancer. This review provides insight into the current developments, recent discoveries, and significant challenges in cancer and aging biomarkers, with a specific focus on their application in advanced age.

Transient receptor potential (TRP) channels are strongly associated with colon cancer development and progression. This study leveraged a multivariate Cox regression model on publicly available datasets to construct a TRP channels-associated gene signature, with further validation of signature in real world samples from our hospital treated patient samples. Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curves were employed to evaluate this gene signature's predictive accuracy and robustness in both training and testing cohorts, respectively. Additionally, the study utilized the CIBERSORT algorithm and single-sample gene set enrichment analysis to explore the signature's immune infiltration landscape and underlying functional implications. The support vector machine algorithm was applied to evaluate the signature's potential in predicting chemotherapy outcomes. The findings unveiled a novel three TRP channels-related gene signature (MCOLN1, TRPM5, and TRPV4) in colon adenocarcinoma (COAD). The ROC and K-M survival curves in the training dataset (AUC = 0.761; p = 1.58e-05) and testing dataset (AUC = 0.699; p = 0.004) showed the signature's robust predictive capability for the overall survival of COAD patients. Analysis of the immune infiltration landscape associated with the signature revealed higher immune infiltration, especially an increased presence of M2 macrophages, in high-risk group patients compared to their low-risk counterparts. High-risk score patients also exhibited potential responsiveness to immune checkpoint inhibitor therapy, evident through increased CD86 and PD-1 expression profiles. Moreover, the TRPM5 gene within the signature was highly expressed in the chemoresistance group (p = 0.00095) and associated with poor prognosis (p = 0.036) in COAD patients, highlighting its role as a hub gene of chemoresistance. Ultimately, this signature emerged as an independent prognosis factor for COAD patients (p = 6.48e-06) and expression of model gene are validated by public data and real-world patients. Overall, this bioinformatics study provides valuable insights into the prognostic implications and potential chemotherapy resistance mechanisms associated with TRPs-related genes in colon cancer.

Background: Transient receptor potential channels (TRPs) have been demonstrated to take on functions in pancreatic adenocarcinoma (PAAD) biology. However, little data are available that validate the potential of TRP in a clinical translational setting. Methods: A TRPs-related gene signature was constructed based on the Cox regression using a TCGA-PAAD cohort and receiver operating characteristic (ROC) was used to evaluate the predictive ability of this model. Core genes of the signature were screened by a protein-to-protein interaction (PPI) network, and expression validated by two independent datasets. The mutation analysis and gene set enrichment analysis (GSEA) were conducted. Virtual interventions screening was performed to discover substance candidates for the identified target genes. Results: A four TRPs-related gene signature, which contained MCOLN1, PKD1, TRPC3, and TRPC7, was developed and the area under the curve (AUC) was 0.758. Kaplan–Meier analysis revealed that patients with elevated signature score classify as a high-risk group featuring significantly shorter recurrence free survival (RFS) time, compared to the low-risk patients (p < 0.001). The gene prediction model also had a good predictive capability for predicting shortened overall survival (OS) and disease-specific survival (DSS) (AUC = 0.680 and AUC = 0.739, respectively). GSEA enrichment revealed the core genes of the signature, TRPC3 and TRPC7, were involved in several cancer-related pathways. TRPC3 mRNA is elevated in cancer tissue compared to control tissue and augmented in tumors with lymph node invasion compared to tumors without signs of lymph node invasion. Virtual substance screening of FDA approved compounds indicates that four small molecular compounds might be potentially selective not only for TRPC3 protein but also as a potential binding partner to TRPC7 protein. Conclusions: Our computational pipeline constructed a four TRP-related gene signature that enables us to predict clinical prognostic value of hitherto unrecognized biomarkers for PAAD. Sensory ion channels TRPC3 and TRPC7 could be the potential therapeutic targets in pancreatic cancer and TRPC3 might be involved in dysregulating mitochondrial functions during PAAD genesis.

Background Treatment options for metastatic colorectal cancer (CRC) are mostly ineffective. We present new evidence that tumor tissue collagen type X alpha 1 (COL10A1) is a relevant candidate biomarker to improve this dilemma. Methods Several public databases had been screened to observe COL10A1 expression in transcriptome levels with cell lines and tissues. Protein interactions and alignment to changes in clinical parameters and immune cell invasion were performed, too. We also used algorithms to build a novel COL10A1-related immunomodulator signature. Various wet-lab experiments were conducted to quantify COL10A1 protein and transcript expression levels in disease and control cell models. Results COL10A1 mRNA levels in tumor material is clinical and molecular prognostic, featuring upregulation compared to non-cancer tissue, increase with histomorphological malignancy grading of the tumor, elevation in tumors that invade perineural areas, or lymph node invasion. Transcriptomic alignment noted a strong positive correlation of COL10A1 with transcriptomic signature of cancer-associated fibroblasts (CAFs) and populations of the immune compartment, namely, B cells and macrophages. We verified those findings in functional assays showing that COL10A1 are decreased in CRC cells compared to fibroblasts, with strongest signal in the cell supernatant of the cells. Conclusion COL10A1 abundance in CRC tissue predicts metastatic and immunogenic properties of the disease. COL10A1 transcription may mediate tumor cell interaction with its stromal microenvironment.

BACKGROUND: In the high-risk, high-stakes specialty of neurosurgery, traditional teaching methods often fail to provide young residents with the proficiency needed to perform complex procedures in stressful situations, with direct effects on patient outcomes. Physical simulators provide the freedom of focused, hands-on training in a more controlled environment. However, the adoption of simulators in neurosurgical training remains a challenge because of high acquisition costs, complex production processes, and lack of realism. OBJECTIVE: To introduce an easily reproducible, cost-effective simulator for external ventricular drain placements through various ventriculostomy approaches with life-like tactile brain characteristics based on real patients' data. METHODS: Whole brain and skull reconstruction from patient's computed tomography and MRI data were achieved using freeware and a desktop 3-dimensional printer. Subsequently, a negative brain silicone mold was created. Based on neurosurgical expertise and rheological measurements of brain tissue, gelatin in various concentrations was tested to cast tactilely realistic brain simulants. A sample group of 16 neurosurgeons and medical students tested and evaluated the simulator in respect to realism, haptics, and general usage, scored on a 5-point Likert scale. RESULTS: We saw a rapid and significant improvement of accuracy among novice medical students. All participants deemed the simulator as highly realistic, effective, and superior to conventional training methods. CONCLUSION: We were able to demonstrate that building and implementing a high-fidelity simulator for one of the most important neurosurgical procedures as an effective educational and training tool is achievable in a timely manner and without extensive investments.