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PubMed2026

Translational Gap in Biomarker Discovery: Tumor Surface Markers Rarely Mirror Circulating Levels.

BACKGROUND: Tumor-associated cell surface proteins are frequently proposed as circulating biomarkers for colorectal cancer (CRC) based on their high tumor expression. However, many candidates identified through tissue-based analyses fail to translate into clinically useful biomarkers. We investigated the translational gap between tissue-level expression and circulating detectability in CRC, focusing on molecular subtypes defined by caudal-type homeobox 2 (CDX2) expression. METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to identify cell surface markers differentially expressed between CDX2-Low and CDX2-High CRCs. A clinical cohort of right-sided CRC patients was evaluated using paired tumor tissue and preoperative plasma samples. CDX2 expression was assessed by immunohistochemistry, and circulating concentrations of selected cell surface proteins were quantified using a multiplex ELISA platform. RESULTS: Several tumor-associated cell surface markers exhibited marked CDX2-dependent differences in tissue expression. However, for most markers, circulating plasma levels did not mirror tissue-level patterns. CEACAM1 was the sole marker demonstrating concordant CDX2-dependent differences in both tumor tissue and plasma, with significantly lower levels in CDX2-Low CRCs. In contrast, CEACAM5 showed a dissociation between tissue expression and circulating levels, despite analytical validation against serum carcinoembryonic antigen (CEA). CONCLUSIONS: Our findings demonstrate that tumor overexpression of cell surface markers does not necessarily translate into detectable circulating biomarkers. This translational disconnect underscores limitations of biomarker selection strategies based solely on tissue expression and highlights the importance of integrating systemic biology into biomarker development. While some tumor-associated proteins may lack utility as circulating biomarkers, they may still represent viable therapeutic targets in CRC.

CDX2↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗

PubMed2026

Association of immune and proliferation gene signatures and stromal tumor-infiltrating lymphocytes with clinical outcomes in patients with stage I triple-negative breast cancer.

BACKGROUND: One-third of patients with triple-negative breast cancer (TNBC) are diagnosed with stage I tumors. Biomarkers to stratify prognosis in this setting remain a major unmet need. METHODS: Tissue samples and clinicopathologic data were retrieved from consecutive patients with stage I TNBC (defined as ER <10% and HER2-negative) who underwent upfront breast surgery and received standard of care adjuvant systemic therapy at Dana-Farber/Brigham Cancer Center between 2016 and 2021. The TNBC-DX assay (Core Immune Gene [CIG] signature, proliferation signature) was applied to tumor tissue, and stromal tumor-infiltrating lymphocytes (sTILs) were centrally reviewed. Both biomarkers were tested for association with clinical outcomes using the Kaplan-Meier method. RESULTS: A total of 253 patients with stage I TNBC were included. Most tumors were ductal (88.9%) and high-grade (73.1%); 65.2% of patients received adjuvant chemotherapy. With 18 recurrence events observed, the 3-year recurrence-free survival (RFS) in the overall cohort was 95.0% (95% confidence interval [CI]: 92.1% - 98.1%) and the 3-year overall survival was 97.9% (95% CI: 95.9% - 100.0%). No significant differences in RFS were observed by TNBC-DX (n = 117 patients) or sTILs (n = 123 patients) category. However, a 3-year RFS of 100% (95% CI: 100% - 100%) was observed among the 29 patients with the highest CIG score quartile. A favorable prognosis was also observed in patients with high sTILs (>20%), who experienced a 3-year RFS of 97.0% (95% CI: 90% - 100%). Conversely, a high TNBC-DX proliferation score was numerically associated with poor outcomes, with a 3-year RFS of 83% (95% CI: 68% - 100%). CONCLUSIONS: In this retrospective study, immune and proliferative features showed opposing prognostic trends in stage I TNBC. Their integration may improve risk stratification and warrants further investigation.

Stromal tumor infiltrating lymphocytes (sTILs)↗

PubMed2026

LLPS-based classification and a novel prognostic signature reveal NRF1 as a therapeutic target in pancreatic cancer.

BACKGROUND: Aberrant liquid-liquid phase separation (LLPS) can alter biomolecular condensate functions and may influence pancreatic tumorigenesis and progression, but the specific role of LLPS regulators in prognosis and the tumor immune microenvironment (TIME) in pancreatic ductal adenocarcinoma (PDAC) remains unclear. METHODS: We integrated transcriptome data of LLPS regulator-related differentially expressed genes (DEGs; n = 298) in a cohort of 176 PDAC patients from TCGA. Three LLPS regulator subtypes (LS1-LS3) were identified through multi-omics analyses, and a prognostic LLPS subtype-related risk model (LRRPC) was developed and validated. Chromatin immunoprecipitation confirmed NRF1 binding to promoters of key risk genes, and in vitro and in vivo experiments assessed the effects of NRF1 targeting on tumor growth. RESULTS: The three LLPS regulator subtypes exhibited significant differences in prognosis, clinical features, genomic alterations, TIME patterns and predicted immunotherapy response. The LRRPC signature predicted prognosis and immunotherapy efficacy across cohorts and was associated with tumor biomarkers and immune infiltration. Nuclear Respiratory Factor 1 (NRF1) directly regulated hub genes such as FAM83A, RHOV and ITGB6, promoting PDAC cell proliferation, while its inhibition induced apoptosis and reduced tumor growth. CONCLUSIONS: This study proposes an LLPS-based stratification framework for PDAC, and the LRRPC model provides an LLPS subtype-related risk score that may assist personalized prognostic assessment and immunotherapy stratification. NRF1 emerges as a promising therapeutic candidate whose targeting can inhibit tumor progression in PDAC experimental models and warrants further evaluation.

Immunotherapy↗

PubMed2025

High Prevalence of Potential Molecular Therapeutic Targets in Poorly Differentiated Thyroid Carcinoma.

Poorly differentiated thyroid carcinoma (PDTC) is a rare thyroid cancer with aggressive clinical course and peculiar clinical/pathological characteristics but lacking effective therapeutic options, when surgery is not curative. We aimed at the molecular characterization of PDTC with a specific focus on the identification of potential therapeutic targets. A series of PDTC cases was selected from a multi-institutional network. Fifty-nine samples underwent wide targeted DNA and RNA next-generation sequencing (NGS) testing and immunohistochemical analysis for mismatch repair (MMR) proteins. Gene fusion analysis was enriched by 25 additional samples. Prevalence of MMR protein loss was 11.9%. The most prevalent mutations were in NRAS (25%) and TP53 (25%), mutually exclusive. TERT promoter (TERTp) mutations were detected in 19.6% of cases (10/51). NRAS-mutated cases were enriched for mutations in genes belonging to the same pathway. TP53-mutated samples lacked TERTp co-mutations, but were associated with mutations in PTEN and in genes related to MMR system and/or loss of MMR proteins. TERTp mutations were the most prevalent alterations (28%, 7/25) in a third group that lacked NRAS or TP53 mutations. Four cases harbored gene fusions, including two cases harboring the TBL1XR1::PIK3CA fusion that has never been reported in thyroid cancer, so far. In conclusion, PDTC may be genomically segregated in subgroups with specific molecular characteristics. Overall, targetable gene fusions have a prevalence of 9% (4/42). Moreover, 47% of cases are potential candidates for individualized target therapies since they harbor mutations in genes coding for potentially targetable molecules and/or have defects in the MMR system.

Humans↗

PubMed2026

Next-Generation Sequencing Completion and Timeliness Using a Reflex Testing Protocol for Patients with Stage II to IV Nonsquamous Non-Small Cell Lung Cancer.

BACKGROUND: Next-generation Sequencing (NGS) is critical for providing treatment recommendations across multiple stages of non-small cell lung cancer (NSCLC). However, a substantial proportion of patients do not undergo testing. This study evaluated the completion rates and timeliness of NGS in patients with stage II to IV NSCLC at a single academic institution with a reflex NGS testing protocol. METHODS: Patients with stage II to IV nonsquamous NSCLC (ns-NSCLC) diagnosed between 2015 and 2022 were identified retrospectively. A reflex, tissue-based testing protocol was initiated in 2015 using in-house NGS. Pyrosequencing was performed if NGS failed. RESULTS: 501 patients were included: 75 (15.0%) with stage II, 82 (16.4%) with stage III, and 344 (68.6%) with stage IV ns-NSCLC. Tissue NGS was completed in 380 (75.8%) patients and 465 (92.8%) completed some tissue-based genomic testing when including pyrosequencing. Median time from biopsy to NGS was 17.0 days (range, 6-61 days). 61.0% of patients had NGS results prior to a first treatment of any type and 88.4% had tissue NGS results prior to systemic therapy. Among stage IV patients with completed NGS, median overall survival was 2.27 years for patients with NGS results prior to first treatment compared to 1.08 years for patients without NGS results prior to treatment initiation (P = .04). CONCLUSIONS: Implementation of an in-house, reflex NGS testing protocol enabled rapid genomic profiling in a high proportion of patients with stage II to IV ns-NSCLC. NGS completion prior to receiving first-line therapy was associated with improved survival compared to completion after first line treatment in stage IV patients.

Humans↗

PubMed2026

Large cell neuroendocrine carcinoma of the lung: Current standards, emerging targets, and translational foundations.

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is one of the most complex and heterogenous clinical entities in thoracic oncology, sharing features with both non-small cell lung cancer (NSLC) and neuroendocrine lung cancers. LCNEC diagnosis and classification relies on evolving histopathological and molecular criteria that define its diagnostic boundaries. Recent advances have confirmed the dual nature of LCNEC, with distinct small cell-like and non-small cell-like molecular characteristics, which guide treatment decisions. In this review, we synthesize current evidence on the diagnosis, molecular characterization, and multimodality management of LCNEC to provide a comprehensive framework for clinical and translational decision-making. A comprehensive literature search was conducted using the PubMed database with no date restrictions, last updated on 12th of April 2026. Articles were selected based on relevance to the diagnosis, molecular characterization, and management of pulmonary LCNEC. Emphasis was placed on studies providing clinical, pathological, and molecular insights into the field. In this review, we summarize contemporary diagnostic approaches, including the expanding role of immunohistochemistry, next‑generation sequencing, and integrated morpho‑molecular assessment. This review represents a consolidated update on LCNEC genomic and transcriptional landscapes, and actionable molecular alterations that are anticipated to impact treatment decisions. Additionally, it provides a state-of-the-art overview of multimodality management, covering surgical approaches, radiotherapy, perioperative therapy, systemic treatment, and the emerging role of immunotherapy. Despite incremental progress, LCNEC remains constrained by limited prospective data and lack of consensus on optimal treatment pathways. By conducting literature review, we identified persistent gaps in LCNEC published data and hereby highlight key priorities for future research.

Humans↗

PubMed2022

Challenges and opportunities associated with the MD Anderson IMPACT2 randomized study in precision oncology.

We investigated the challenges of conducting IMPACT2, an ongoing randomized study that evaluates molecular testing and targeted therapy (ClinicalTrials.gov: NCT02152254). Patients with metastatic cancer underwent tumor profiling and were randomized between the two arms when eligibility criteria were met (Part A). In Part B, patients who declined randomization could choose the study arm. In Part A, 69 (21.8%) of 317 patients were randomized; 78.2% were not randomized because of non-targetable alterations (39.8%), unavailability of clinical trial (21.8%), other reasons (12.6%), or availability of US Food and Drug Administration (FDA)-approved drugs for the indication (4.1%). In Part B, 32 (20.4%) of 157 patients were offered randomization; 16 accepted and 16 selected their treatment arm; 79.0% were not randomized (patient's/physician's choice, 29.3%; treatment selection prior to genomic reports, 16.6%; worsening performance status/death, 12.7%; unavailability of clinical trials, 6.4%; other, 6.4%; non-targetable alterations, 5.7%; or availability of FDA-approved drugs for the indication, 1.9%). In conclusion, although randomized controlled trials have been considered the gold standard for drug development, the execution of randomized trials in precision oncology in the advanced metastatic setting is complicated. We encountered various challenges conducting the IMPACT2 study, a large precision oncology trial in patients with diverse solid tumor types. The adaptive design of IMPACT2 enables patient randomization despite the continual FDA approval of targeted therapies, the evolving tumor biomarker landscape, and the plethora of investigational drugs. Outcomes for randomized patients are awaited.

Journal Article↗

PubMed2026

Conserved miRNA regulators of PD-1/PD-L1 in glioblastoma and colorectal cancer.

Immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 axis have transformed cancer therapy, but their efficacy remains limited in glioblastoma (GBM) and heterogeneous in colorectal cancer (CRC). MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level, including immune checkpoint molecules, yet conserved regulatory miRNA networks across distinct cancers remain poorly defined. Five conserved miRNAs (miR-106a-5p, miR-106b-5p, miR-20a-5p, miR-20b-5p, miR-138-5p) fulfilled the selection criteria and were consistently dysregulated in GBM and CRC. MiR-106a-5p and miR-106b-5p were upregulated in both cancers and showed favourable prognostic associations, with higher expression correlating with improved survival. miR-20a-5p and miR-20b-5p were preferentially expressed in microsatellite-stable (MSS) CRC and correlated with favourable outcomes in both cancers, whereas miR-138-5p was downregulated in both tumours compared to normal tissue, but showed opposite survival associations, with higher levels linked to worse prognosis. Correlation analysis revealed significant inverse associations between several miRNAs and checkpoint gene expression, including moderate inverse correlations for CD274-miR-106a-5p in GBM, CD274-miR-20a-5p in CRC and PDCD1LG2-miR-20a-5p in both cancers. Pan-cancer profiling demonstrated broad and heterogeneous dysregulation, with expression absent in ovarian cancer for four of the five miRNAs. Pathway enrichment implicated the TGF-β, Hippo, FoxO, and cell cycle pathways, consistent with their known roles in tumour immune evasion. We identified a conserved set of miRNAs that are dysregulated in both GBM and CRC, correlate with survival, and display inverse relationships with PD-1/PD-L1/PD-L2 expression. These miRNAs represent candidate regulators of the PD-1/PD-L1/PD-L2 axis and potential biomarkers of tumour biology that may influence immune checkpoint signalling.

Humans↗

PubMed2026

Establishment of a multi-targeted magnetic combined enrichment system for circulating tumor cells in gastric cancer and analysis of their genomic profiles.

Background: This study aims to establish an efficient Circulating tumor cells (CTCs) multi-targeted magnetic combined sorting system for Gastric cancer (GC), while comparing it with tissue and circulating tumor DNA (ctDNA) samples to evaluate its feasibility and consistency for genomic profiling analysis. Method: Establish an efficient CTCs sorting system for GC targeting epithelial cell adhesion molecule, cell surface vimentin, and protein tyrosine kinase 7, and evaluate its physicochemical properties and cell capture efficiency. Assess the feasibility of tumor cell detection through animal experiments. Sixty-eight GC patients underwent CTCs detection. Clinical information was analyzed to evaluate the clinical utility of CTCs in the auxiliary diagnosis of GC. Next-generation sequencing was performed on GC tissue, CTCs, and ctDNA samples to assess the consistency of genetic mutations across different sample types. Results: The constructed CTCs sorting system exhibits excellent physicochemical properties, achieving a capture rate of 94.68%. Animal studies confirm a positive correlation between tumor cells count and tumor volume. The number of CTCs in the blood of GC patients is significantly correlated with tumor size, stage, and metastasis. The CTCs count in GC patients is significantly higher than in healthy individuals and high-risk groups for cancer, with diagnostic sensitivity and specificity of 97.29% and 97.73%, respectively. The mutation detection rate in CTCs samples was significantly higher than that in tissue and ctDNA samples. The concordance rate between CTCs and tissue mutations was 24.32%, while the concordance rate between CTCs and ctDNA mutations was 19.05%. Conclusion: This study successfully established a multi-target combined CTCs multi-targeted magnetic combined sorting system for GC. CTCs detection based on this system can be used for the auxiliary diagnosis of GC patients. Furthermore, compared to GC tissue and ctDNA samples, CTCs detection enables more comprehensive genomic profiling analysis and serves as an important supplement to GC genomic analysis.

Humans↗

PubMed2025

Association of metabolic dysregulation with treatment response in rectal cancer patients undergoing chemoradiotherapy.

BACKGROUND: This study aimed to explore the metabolic changes during neoadjuvant chemoradiotherapy (NCRT) in patients with locally advanced rectal cancer (LARC) by serum metabolomics analysis, and to provide new biomarkers for individualized treatment and efficacy prediction. METHODS: Serum samples from 20 patients with LARC before, during and after NCRT were collected for metabolomic analysis. The metabolites in the serum samples were analyzed qualitatively and quantitatively using gas chromatography-mass spectrometry (GC-MS). Meanwhile, the differences in metabolic profiles at different time points were compared and significantly changed metabolites were screened. RESULTS: The metabolic profiles of patients were significantly altered at different time points of NCRT. Through metabolomic analysis, we identified metabolites that were significantly altered during NCRT and revealed alterations in the associated metabolic pathways. The predictive power of pre-radiotherapy isocitric acid and pro-radiotherapy 3-hydroxy-3-(4'-hydroxy-3'-methoxyphenyl) propionic acid in distinguishing patients sensitive and non-sensitive to NCRT was markedly high, with AUC values of 0.875 and 0.75, respectively. Additional analysis indicated that a combined panel of serum metabolites yielded even higher AUC values, thereby enhancing the accuracy of predicting the efficacy of neoadjuvant NCRT. CONCLUSION: This study revealed metabolic changes and corresponding alterations in metabolic pathways during NCRT in patients with LARC by serum metabolomic analysis. The metabolic disorders may be associated with poor outcomes in patients treated with NCRT for rectal cancer, providing new biomarkers for individualized treatment and prognostic assessment. Further studies and validation will help to gain insight into the mechanism of these metabolic changes and provide more basis for clinical application.

Humans↗

PubMed2025

Liver cancer-specific prognostic model developed using endoplasmic reticulum stress-related LncRNAs and LINC01011 as a potential therapeutic target.

Liver cancer is a serious malignancy worldwide, and long noncoding RNAs (lncRNAs) have been implicated in its prognosis.It remains unclear how lncRNAs related to endoplasmic reticulum stress (ERS) influence liver cancer prognosis. Here, we analyzed RNA and clinical data from the Cancer Genome Atlas and sourced ERS-related genes from the Molecular Signatures Database. Co-expression analysis identified ERS-related lncRNAs, and Cox regression analysis as well as least absolute shrinkage and selection operator regression highlighted three lncRNAs for a prognostic model. Based on median risk scores, we classified patients into two risk groups. The high-risk group displayed poor prognosis, and this finding was validated in the test set. According to consistency clustering, the patients were assigned to two clusters, and tumor microenvironment scores were computed. Patients with a high mutation burden had worse outcomes. Furthermore, immune infiltration analysis indicated more immune cells and mutations in checkpoint molecules among high-risk individuals. Drug sensitivity varied between the risk groups. LINC01011 was selected for functional assays. Colony formation assay and CCK-8 assay revealed that silencing LINC01011 suppressed liver cancer cell proliferation. Transwell and scratch assays indicated that silencing LINC01011 inhibited liver cancer cell migration. Western blotting assay revealed that inhibiting LINC01011 induced apoptosis and simultaneously inhibited epithelial-mesenchymal transition. These findings confirm the validity of the prognostic model and indicate that LINC01011 could serve as a potential research target.

Humans↗

PubMed2026

Participant Heterogeneity in the Prostate Cancer Biobank of the NRG: An Obstacle to Broadening the Reach of Precision Oncology.

PURPOSE: Precision medicine has revolutionized oncology; however, tumor biomarkers are not reflective of the heterogeneous cancer population. We evaluated NRG Oncology prostate cancer (PCa) clinical trials for demographic differences among patients with optional biospecimen collection (BC) consent and biospecimen submission (BSub). METHODS: Data from 19 NRG PCa clinical trials closed before 2015 were analyzed. Patients who consented to BC and completed BSub were evaluated by race, ethnicity, median income, area deprivation index (ADI; categorized as highest v lowest three quartiles), age at enrollment, site, and year of enrollment. T/chi-square tests were used for continuous/categorical variables, respectively, followed by logistic regression. RESULTS: Of the 15,648 randomized patients eligible for BC, 11,796 (75%) had specimens submitted. In all, 4,598 (82.2%) of 5,597 eligible patients consented for optional BC in nine clinical trials with a separate BC consent process (consent rates by race/ethnicity: 74.1% Black, 72.8% Hispanic/Latino, 83.8% White). A smaller proportion of Black and Hispanic/Latino patients consented to optional BC compared with those who did not (12.1% v 19.5% Black, P < .0001; 3.5% v 5.8% Hispanic, P = .0006). In univariable logistic regression models, high ADI (more socioeconomic disadvantage) was associated with a decreased likelihood for optional BC consent (odds ratio [OR], 0.67 [95% CI, 0.55 to 0.82]; P = .02), but not a decreased likelihood for BSub (OR, 0.74 [95% CI, 0.53 to 1.04]; P = .08). Multivariable models demonstrated that Black/Hispanic/Latino patients were less likely to consent to optional BC, and Black patients were less likely to have BSub (P < .05 for all). CONCLUSION: White/non-Hispanic patients and those with less socioeconomic disadvantage were more likely to consent to optional BC, whereas Black patients were less likely to have BSub. Targeted solutions are needed to improve biorepository representation so that precision medicine approaches better reflect the cancer population.

Aged↗

PubMed2026

Integrated multi-omics analysis of metabolomics and proteomics uncovers dysregulated amino acid metabolism in HCC metastasis.

BACKGROUND: Metastasis is the primary cause of treatment failure and adverse prognosis in hepatocellular carcinoma (HCC), and the molecular basis of HCC metastasis remains poorly defined. This work investigated the potential mechanisms underlying HCC metastasis through integrated multi-omics analysis of metabolomics and proteomics. METHOD: This retrospective study included 105 individuals with HCC, with comparative analysis between metastatic and non-metastatic cases. We further evaluated the effects of metastasis on serum metabolomics and proteomics in HCC patients. RESULT: Widespread disturbances in amino acid metabolism were identified via untargeted metabolomics in HCC patients with metastasis, closely governing inflammation-related metabolic remodeling and oxidative stress responses. Specifically, we identified 91 and 59 distinct differential metabolites capable of indicating HCC metastasis, with the screening criteria set as log2 fold change > 1.5, adjusted P value < 0.05, and VIP > 1.5 in positive and negative modes, respectively. The alanine, aspartate and glutamate metabolism pathway correlated with HCC-associated lung metastasis, while the gluconeogenesis pathway was linked to HCC-associated bone metastasis. Compared with HCC (non-metastatic hepatocellular carcinoma), the key molecular alterations in the multi-omics network of HCC_M (HCC with metastasis) are implicated in inflammatory metabolic reprogramming, oxidative stress response, gluconeogenesis, glycolysis, and the tricarboxylic acid (TCA) cycle. Twenty-five proteins, including PKM2, PERCK, ALDH2, CPS1, GLS1, GLUD1, GOT1, and SLC38A2, were identified as potential biomarkers for HCC metastasis. CONCLUSION: By integrating untargeted metabolomic and proteomic profiling, we identified distinct metabolic and proteomic changes linked to HCC metastasis. This work also characterized the pathological characteristics and core pathways underlying HCC metastasis, while identifying potential therapeutic candidates.

Humans↗

PubMed2026

"Updates on diagnostic and prognostic molecular biomarkers of CNS tumors".

The diagnosis and classification of central nervous system (CNS) tumors has undergone a paradigm shift over the past decade, evolving from a purely histology-based approach to an integrated framework that incorporates molecular and epigenetic features. This review summarizes recent updates in key genomic and epigenomic biomarkers across major CNS tumor categories, with a focus on their diagnostic, prognostic, and therapeutic implications. DNA methylation profiling has emerged as a valuable tool for tumor classification, subgrouping, and grading, complementing traditional histopathologic assessment. Across diffuse gliomas, newly characterized molecular alterations have refined grading criteria and clarified the boundaries between tumor types, including important caveats about the use of individual molecular features as sole diagnostic criteria. In ependymomas, medulloblastomas, atypical teratoid/rhabdoid tumors, meningiomas, pineal tumors, and embryonal tumors, methylation profiling now defines biologically and clinically meaningful subgroups that inform risk stratification and treatment selection. The emerging recognition of mismatch repair-deficient gliomas and fusion-driven tumor entities further underscores the expanding complexity of CNS tumor taxonomy. As molecular technologies continue to advance, the integration of genomic, epigenomic, histopathologic, and clinical data will be essential to improving diagnostic precision, guiding therapy, and ultimately enhancing patient outcomes.

Embryonal↗

PubMed2024

Mutant KRAS in Circulating Tumor DNA as a Biomarker in Localized Pancreatic Cancer Patients Treated With Neoadjuvant Chemotherapy.

OBJECTIVE: The primary objective was to determine the prognostic significance of circulating tumor DNA (ctDNA) in patients receiving neoadjuvant chemotherapy (NAC) for localized pancreatic ductal adenocarcinoma (PDAC) using digital droplet polymerase chain reaction (ddPCR). BACKGROUND: Increasingly, ctDNA is being used for clinical decision-making in a variety of solid malignancies. However, the detection and prognostic value of KRAS ctDNA as assessed by ddPCR during NAC for PDAC has yet to be characterized. METHODS: Patients with localized PDAC eligible to receive NAC were prospectively enrolled. Peripheral blood samples were obtained at diagnosis, after NAC, and after resection and analyzed for ctDNA using ddPCR. Log-rank tests and Cox proportional hazards model were used to assess for associations with OS. RESULTS: Eighty-four patients were included in the analysis. Mutant KRAS ctDNA was detected in 49.3% of patients at diagnosis, 69.6% of patients after NAC, and 69.7% of patients after resection, respectively. There were 15 (17.9%) patients who cleared mutational ctDNA over the course of treatment. Clearance of ctDNA during NAC was associated with improved overall survival (OS) (18.4 mo. vs NR, P <0.05). Detection of mutant KRAS G12V after NAC and resection was associated with shorter OS (18.0 mo vs NR, P <0.031). Detection of the KRAS G12V mutation after resection was associated with reduced OS (aHR 36.75, 95% CI: 2.93-461.38). CONCLUSIONS: Throughout treatment, KRAS ctDNA is detectable by ddPCR in patients with localized PDAC treated with NAC. Detection of mutant KRAS G12V after resection was associated with reduced OS.

Humans↗

PubMed2025

Genomic profiling of aggressive pathologic features in lung adenocarcinoma.

INTRODUCTION: Pathologic features involving LVI (lympho-vascular invasion), PNI (perineural invasion), STAS (spread through air spaces), and Grade 3 pattern (from the International Association for the Study of Lung Cancer grading system) are related to having an aggressive phenotype and linked to poor prognosis. However, few studies have conducted in-depth analyses of these features simultaneously with genomic profiling. METHODS: A total of 1559 sequencing of adenocarcinoma samples were included in the common driver mutations analysis, 1306 samples were brought into genomic mapping analysis. OncoSG's East Asian ancestry dataset was implemented for Tumor-Node-Metastasis-Biomarker (TNMB) classification and prognostic assessment. RESULTS: EGFR was more significantly prevalent in LVI negativity (P = 0.021), STAS negativity (P = 0.002), and moderate grade (P < 0.001). ALK was significantly interrelated with LVI (P = 0.028), STAS (P < 0.001), and poor grade (P < 0.001); ROS1 and STAS positivity (P = 0.031), poor grade (P = 0.016) were significantly related. KRAS (P = 0.003) and BRAF-V600E (P = 0.002) were only significantly intertwined with poor grade. Apart from common driver mutations, TP53, CHEK2, KEAP1, PTEN, RB1, NF1 were significantly enriched in LVI samples (P < 0.05). TP53, PTEN, CTNNB1, HGF, NF1 were more prominent in STAS (P < 0.01). TP53, LRP1B, NF1 were significantly more prevalent in Grade 3 pattern (P < 0.001). The mixture of STK11, PTEN, and TOP2A generated by exclusive mutations may be a potential predictor of TNMB categorization towards survival. The HR of stage II compared I of TNMB was 2.28 (95 % CI 1.36-3.86, P < 0.001), while stage III compared II was 1.95 (95 % CI 1.04-3.21, P = 0.031). CONCLUSIONS: This analysis demonstrated the correlation of pathologic features with common driver mutations, key mutations and canonical oncogenic signaling pathways. The data highlighted the similarities and differences among these features horizontally, and provide new insights in TNMB classification and prognostic assessment.

Humans↗

PubMed2026

ITPRIPL1: A tumor immune-associated biomarker with prognostic and therapeutic implications in gastrointestinal cancer.

Inositol 1,4,5-trisphosphate receptor-interacting protein-like 1(ITPRIPL1) has recently been implicated in tumor-immune regulation, yet its tumor-type specificity and clinical relevance in gastrointestinal malignancies remain unclear. Here, we performed an integrative analysis of ITPRIPL1 across stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), rectal adenocarcinoma (READ), and esophageal carcinoma (ESCA) using bulk transcriptomics, immune pathway analyses, survival modeling, single-cell RNA sequencing, immunofluorescence validation, and therapeutic correlation analyses. Although ITPRIPL1 was upregulated across gastrointestinal cancers, its prognostic significance was highly tumor-specific, with elevated expression consistently predicting unfavorable survival only in STAD. In gastric cancer, ITPRIPL1 expression was closely associated with immune-related pathways and genomic instability features, and its prognostic association varied across immune contexts, particularly according to CD8⁺/CD4⁺ T-cell abundance, with an exploratory association also observed for zeta-chain-associated protein kinase 70 (ZAP70) expression. Single-cell and immunofluorescence analyses demonstrated preferential enrichment of ITPRIPL1 in T cells and tumor-adjacent immune structures. Notably, Exploratory analyses further showed that higher ITPRIPL1 expression was associated with favorable survival outcomes in selected external pretreatment immunotherapy cohorts and with lower IC50 values for several agents in cancer cell-line pharmacogenomic datasets. Collectively, these findings identify ITPRIPL1 as an immune-associated biomarker with primary clinical relevance in gastric cancer.

Humans↗