[Colorectal adenocarcinoma with enteroblastic differentiation: a clinicopathological analysis of eight cases].

Objective: To investigate the clinicopathological features of colorectal adenocarcinoma with enteroblastic differentiation (CAED). Methods: Eight cases of CAED diagnosed at the Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China from January 2017 to August 2023 were collected. The histopathological, immunohistochemical, molecular and prognostic features of 8 CAED cases were analyzed. The relevant studies were also reviewed. Results: Among the eight patients, there were six males and two females, with an average age of 58 years (range: 29-77 years, median age: 61.5 years). Preoperative serum alpha-fetoprotein levels were elevated in five patients (14.0-286.6 µg/L). Four tumors were located in the colon, and four tumors in the rectum. Two patients were clinically staged as advanced stage (stage Ⅳ), and distant metastasis occurred at the initial diagnosis (one case had liver metastasis, and the other had lung, bone and multiple lymph nodes metastases). Six patients were clinically staged as locally-advanced stage (Stage Ⅱ-Ⅲ). Three of them developed distant metastases after surgery (one case had liver metastasis, one case had lung metastasis, and one case had peritoneal metastasis). Additionally, two patients died at 9 months and 24 months after surgery, respectively. The tumors were composed of various proportions of adenocarcinoma components with enteroblastic differentiation (30%-100%) and classical tubular adenocarcinoma components. The component with enteroblastic differentiation exhibited morphology similar to embryonic intestinal epithelium: cuboidal or columnar tumor cells arranged in tubular, papillary, cribriform, or solid nest patterns, with clear cytoplasm. Immunohistochemical studies showed that tumor cells expressed at least one oncofetal protein (SALL4, Glypican-3, and AFP). In addition, focal squamous differentiation was observed in 3 cases (3/8). Compared to the primary tumor, both CAED and squamous differentiation components were increased in the metastatic tumors. Based on the sequencing results of KRAS, NRAS and BRAF of the primary and/or metastatic tumors, 5 cases were wild-type, while KRAS exon 2 (G13D) mutations were identified in 2 cases. Conclusions: CAED is a rare colorectal malignancy with a dismal prognosis. Accurate pathological diagnosis is prognostically valuable. The histological features of enteroblastic differentiation, elevated serum AFP levels, and the expression of oncofetal proteins play an important role in the tumor diagnosis.

Pre-operative plasma VEGF-C levels portend recurrence in epithelial ovarian cancer patients and is a bankable prognostic marker even in the initial assessment of a patient.

PURPOSE: Our explorative study assessed a panel of molecules for their association with epithelial ovarian carcinomas and their prognostic implications. The panel included tissue expression of VEGF-C, COX-2, Ki-67 and eNOS alongside plasma levels of VEGF-C and nitric oxide. METHODS: 130 cases were enrolled in the study. Plasma levels were quantified by ELISA and tissue expressions were scored by immunohistochemistry. The Chi square and Fischer's exact test were applied to examine the impact of markers on clinicopathological factors. Non-parametric Spearman's rank correlation test was applied to define the association among test factors. RESULTS: Plasma VEGF-C levels and COX-2 tissue expression strongly predicted recurrence and poor prognosis (< 0.001). Tissue Ki-67 was strongly indicative of late-stage disease (< 0.001). The aforementioned markers significantly associated with clinicopathological factors. Nuclear staining of VEGF-C was intriguing and was observed to correlate with high grade-stage malignancies, highly elevated plasma VEGF-C, and with recurrence. eNOS tissue expression showed no significant impact while nitric oxide associated positively with ascites levels. Tissue expression of VEGF-C did not associate significantly with poor prognosis although the expression was highly upregulated in most of the cases. CONCLUSION: Plasma VEGF-C holds immense promise as a prognostic marker and the nuclear staining of VEGF-C seems to have some significant implication in molecular carcinogenesis and is a novel finding that commands further robust scrutiny. We present a first such study that assesses a set of biomarkers for prognostic implications in clinical management of epithelial ovarian carcinomas in a pan-Indian (Asian) population.

Identification of Potential Crucial Biomarkers in STEMI Through Integrated Bioinformatic Analysis. / Identificação de Potenciais Biomarcadores Cruciais em IAMCSST por Meio de Análise Bioinformática Integrada.

BACKGROUND: ST-segment elevation myocardial infarction (STEMI) is one of the leading causes of fatal cardiovascular diseases, which have been the prime cause of mortality worldwide. Diagnosis in the early phase would benefit clinical intervention and prognosis, but the exploration of the biomarkers of STEMI is still lacking. OBJECTIVES: In this study, we conducted a bioinformatics analysis to identify potential crucial biomarkers in the progress of STEMI. METHODS: We obtained GSE59867 for STEMI and stable coronary artery disease (SCAD) patients. Differentially expressed genes (DEGs) were screened with the threshold of |log2fold change| > 0.5 and p <0.05. Based on these genes, we conducted enrichment analysis to explore the potential relevance between genes and to screen hub genes. Subsequently, hub genes were analyzed to detect related miRNAs and DAVID to detect transcription factors for further analysis. Finally, GSE62646 was utilized to assess DEGs specificity, with genes demonstrating AUC results exceeding 75%, indicating their potential as candidate biomarkers. RESULTS: 133 DEGs between SCAD and STEMI were obtained. Then, the PPI network of DEGs was constructed using String and Cytoscape, and further analysis determined hub genes and 6 molecular complexes. Functional enrichment analysis of the DEGs suggests that pathways related to inflammation, metabolism, and immunity play a pivotal role in the progression from SCAD to STEMI. Besides, related-miRNAs were predicted, has-miR-124, has-miR-130a/b, and has-miR-301a/b regulated the expression of the largest number of genes. Meanwhile, Transcription factors analysis indicate that EVI1, AML1, GATA1, and PPARG are the most enriched gene. Finally, ROC curves demonstrate that MS4A3, KLRC4, KLRD1, AQP9, and CD14 exhibit both high sensitivity and specificity in predicting STEMI. CONCLUSIONS: This study revealed that immunity, metabolism, and inflammation are involved in the development of STEMI derived from SCAD, and 6 genes, including MS4A3, KLRC4, KLRD1, AQP9, CD14, and CCR1, could be employed as candidate biomarkers to STEMI.

FUNDAMENTO: O infarto do miocárdio com elevação do segmento ST (IAMCSST) é uma das principais causas de doenças cardiovasculares fatais, que têm sido a principal causa de mortalidade em todo o mundo. O diagnóstico na fase inicial beneficiaria a intervenção clínica e o prognóstico, mas ainda falta a exploração dos biomarcadores do IAMCSST. OBJETIVOS: Neste estudo, conduzimos uma análise bioinformática para identificar potenciais biomarcadores cruciais no progresso do IAMCSST. MÉTODOS: Obtivemos GSE59867 para pacientes com IAMCSST e doença arterial coronariana estável (DACE). Genes diferencialmente expressos (GDEs) foram selecionados com o limiar de |log2fold change| > 0,5 e p < 0,05. Com base nesses genes, conduzimos análises de enriquecimento para explorar a relevância potencial entre genes e para rastrear genes centrais. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. RESULTADOS: 133 GDEs entre DACE e IAMCSST foram obtidos. Em seguida, a rede PPI de GDEs foi construída usando String e Cytoscape, e análises posteriores determinaram genes centrais e 6 complexos moleculares. A análise de enriquecimento funcional dos GDEs sugere que as vias relacionadas à inflamação, metabolismo e imunidade desempenham um papel fundamental na progressão de DACE para IAMCSST. Além disso, foram previstos miRNAs relacionados, has-miR-124, has-miR-130a/b e has-miR-301a/b regularam a expressão do maior número de genes. Enquanto isso, a análise dos fatores de transcrição indica que EVI1, AML1, GATA1 e PPARG são os genes mais enriquecidos. Finalmente, as curvas ROC demonstram que MS4A3, KLRC4, KLRD1, AQP9 e CD14 exibem alta sensibilidade e especificidade na previsão de IAMCSST. CONCLUSÕES: Este estudo revelou que imunidade, metabolismo e inflamação estão envolvidos no desenvolvimento de IAMCSST derivado de DACE, e 6 genes, incluindo MS4A3, KLRC4, KLRD1, AQP9, CD14 e CCR1, poderiam ser empregados como candidatos a biomarcadores para IAMCSST.

Comprehensive analysis of fibroblast activation protein expression across 23 tumor indications: insights for biomarker development in cancer immunotherapies.

Introduction: Fibroblast activation protein (FAP) is predominantly upregulated in various tumor microenvironments and scarcely expressed in normal tissues. Methods: We analyzed FAP across 1216 tissue samples covering 23 tumor types and 70 subtypes. Results: Elevated FAP levels were notable in breast, pancreatic, esophageal, and lung cancers. Using immunohistochemistry and RNAseq, a correlation between FAP gene and protein expression was found. Evaluating FAP's clinical significance, we assessed 29 cohorts from 12 clinical trials, including both mono and combination therapies with the PD-L1 inhibitor atezolizumab and chemotherapy. A trend links higher FAP expression to poorer prognosis, particularly in RCC, across both treatment arms. However, four cohorts showed improved survival with high FAP, while in four others, FAP had no apparent survival impact. Conclusions: Our results emphasize FAP's multifaceted role in therapy response, suggesting its potential as a cancer immunotherapy biomarker.

Unlocking the potential: A novel prognostic index signature for acute myeloid leukemia.

Acute myeloid leukemia (AML) is an aggressive malignancy characterized by challenges in treatment, including drug resistance and frequent relapse. Recent research highlights the crucial roles of tumor microenvironment (TME) in assisting tumor cell immune escape and promoting tumor aggressiveness. This study delves into the interplay between AML and TME. Through the exploration of potential driver genes, we constructed an AML prognostic index (AMLPI). Cross-platform data and multi-dimensional internal and external validations confirmed that the AMLPI outperforms existing models in terms of areas under the receiver operating characteristic curves, concordance index values, and net benefits. High AMLPIs in AML patients were indicative of unfavorable prognostic outcomes. Immune analyses revealed that the high-AMLPI samples exhibit higher expression of HLA-family genes and immune checkpoint genes (including PD1 and CTLA4), along with lower T cell infiltration and higher macrophage infiltration. Genetic variation analyses revealed that the high-AMLPI samples associate with adverse variation events, including TP53 mutations, secondary NPM1 co-mutations, and copy number deletions. Biological interpretation indicated that ALDH2 and SPATS2L contribute significantly to AML patient survival, and their abnormal expression correlates with DNA methylation at cg12142865 and cg11912272. Drug response analyses revealed that different AMLPI samples tend to have different clinical selections, with low-AMLPI samples being more likely to benefit from immunotherapy. Finally, to facilitate broader access to our findings, a user-friendly and publicly accessible webserver was established and available at http://bioinfor.imu.edu.cn/amlpi. This server provides tools including TME-related AML driver genes mining, AMLPI construction, multi-dimensional validations, AML patients risk assessment, and figures drawing.

Endogenous estrogen metabolites as oxidative stress mediators and endometrial cancer biomarkers.

BACKGROUND: Endometrial cancer is the most common gynecologic malignancy found in developed countries. Because therapy can be curative at first, early detection and diagnosis are crucial for successful treatment. Early diagnosis allows patients to avoid radical therapies and offers conservative management options. There are currently no proven biomarkers that predict the risk of disease occurrence, enable early identification or support prognostic evaluation. Consequently, there is increasing interest in discovering sensitive and specific biomarkers for the detection of endometrial cancer using noninvasive approaches. CONTENT: Hormonal imbalance caused by unopposed estrogen affects the expression of genes involved in cell proliferation and apoptosis, which can lead to uncontrolled cell growth and carcinogenesis. In addition, due to their ability to cause oxidative stress, estradiol metabolites have both carcinogenic and anticarcinogenic properties. Catechol estrogens are converted to reactive quinones, resulting in oxidative DNA damage that can initiate the carcinogenic process. The molecular anticancer mechanisms are still not fully understood, but it has been established that some estradiol metabolites generate reactive oxygen species and reactive nitrogen species, resulting in nitro-oxidative stress that causes cancer cell cycle arrest or cell death. Therefore, identifying biomarkers that reflect this hormonal imbalance and the presence of endometrial cancer in minimally invasive or noninvasive samples such as blood or urine could significantly improve early detection and treatment outcomes.

Clinical performance and utility of a noninvasive urine-based methylation biomarker: TWIST1/Vimentin to detect urothelial carcinoma of the bladder.

Traditional clinical modalities for diagnosing bladder urothelial carcinoma (BUC) remain limited due to their invasive nature, significant costs, discomfort associated with cystoscopy, and low sensitivity to urine cytology. Therefore, there is an urgent need to identify highly sensitive, specific, and noninvasive biomarkers for the early detection of this neoplasm. Hypermethylated TWIST1/Vimentin promoter may be a noninvasive biomarker using urine sample. We assessed the TWIST1/Vimentin promoter methylation status in urine samples using the Methylated Human TWIST1 and Vimentin Gene Detection Kit (Jiangsu MicroDiag Biomedicine Co., Ltd., China). The samples were collected from five groups: group 1 consisted of patients with BUC, group 2 contained other patients with urologic tumors, group 3 consisted of patients with benign diseases (e.g., urinary tract infections, lithiasis, and benign prostatic hyperplasia), Group 4 included UTUC (upper tract urothelial carcinoma) patients and group5 comprised healthy individuals. The study encompassed 77 BUC patients, and we evaluated the degree of methylation of the TWIST1/Vimentin gene in their urine samples. Notably, TWIST1/Vimentin positivity was significantly elevated in comparison to groups 2, 3 and 5 (all p < 0.001) at a rate of 77.9%, but no significant difference was observed when compared to group 4. In the relationship between TWIST1/Vimentin methylation and clinicopathological features of BC patients from our center, we found there was no significant association between TWIST1/Vimentin status and proteinuria and/or hematuria, and hypermethylation of TWIST1 / VIM genes was found in both high and low tumor grade and in both non-muscle invasive bladder cancer (stages Tis, Ta, or T1) and muscle-invasive bladder cancer (stage T2 or above). In the multivariable analysis for cancer detection, a positive TWIST1/Vimentin methylation were significantly linked to a heightened risk of BC. Moreover, TWIST1/Vimentin promoter methylation demonstrated an ability to detect BUC in urine samples with a sensitivity of 78% and a specificity of 83%. Our findings reveal that hypermethylation of the TWIST1/Vimentin promoter occurs in bladder urothelial carcinoma, and its high sensitivity and specificity suggest its potential as a screening and therapeutic biomarker for urothelial carcinoma of the bladder.

The CXCR4 might be a potential biomarker for esophageal squamous cell carcinoma: A meta-analysis.

OBJECTIVE: To evaluate the relationship between CXCL12/CXCR4 and the progress, prognosis of esophageal squamous cell carcinoma (ESCC), providing evidence for potential early diagnosis, clinical treatment, prognosis evaluation, and therapeutic target of ESCC. METHODS: Databases of PubMed, the Cochrane Library, Embase, and Web of Science were searched for the relationship between CXCL12/CXCR4 and clinicopathological characteristics and survival time of ESCC. Stata16.0 software was used to conduct meta-analysis. RESULTS: A total of 10 studies involving 1216 cases of patients with ESCC were included in our study. The results indicated that high-level expression of CXCR4 was significantly correlated with tumor differentiation [OR = 0.69, 95% confidence interval (CI): (0.50, 0.97)], tumor infiltration [OR = 0.39, 95% CI: (0.25, 0.61)], lymph node metastasis [OR = 0.36, 95% CI: (0.21, 0.61)], clinical stage [OR = 0.33, 95% CI: (0.24, 0.45)] of ESCC. The expression of CXCR4 was also significantly correlated with OS [HR = 2.00, 95% CI: (1.63, 2.45)] and disease-free survival [HR = 1.76, 95% CI: (1.44, 2.15)] in patients of ESCC after surgical resection. No significant relationship was observed between the expression of CXCL12 and the clinicopathological characteristics of ESCC. CONCLUSION: CXCR4 might be a potential biomarker for the progress and prognosis evaluation, and therapeutic target for ESCC.

Significance of Estrogen/Progesterone Receptor Expression in Metaplastic Breast Carcinoma.

Introduction: Metaplastic breast carcinoma (MBC) is a rare subgroup of breast neoplasms associated with adverse outcomes because of its aggressive nature. Typically, MBCs show triple-negative hormone receptor (HR) status. Determining the HR status of breast cancer is an integral part because it is an important prognostic factor and helps in the treatment course of the disease. This study aimed to determine the HR status of MBC, its significance, and its association with various clinicopathological parameters. Methods: This was a retrospective study conducted at the Department of Histopathology, Liaquat National Hospital. A total of 140 biopsy-proven cases of MBC were enrolled in the study. Clinical and pathological data were retrieved from the institutes' archives. Immunohistochemical studies were conducted to determine the estrogen receptor (ER) and progesterone receptor (PR) status. Results: The mean age of MBC in our population was found to be 52.18 ± 12.19 years. The HR positivity rate in our population was found to be 32.9%. A significant association was found between HR status and tumor laterality, tumor size, tumor grade, tumor stage, and recurrence. ER/PR-negative MBCs were most probably associated with higher grade and higher tumor stage and were larger in size (6.62 ± 3.43 cm) than ER/PR-positive MBCs (4.20 ± 1.88 cm). Moreover, ER/PR-positive MBCs showed a higher recurrence rate than ER/PR-negative MBCs (43.5% vs. 25.5%, respectively). No statistically significant relationship was found between HR status and patient age, histological subtype, or survival rate. Conclusion: MBC is a rare breast neoplasm. MBC was found to be triple negative in most cases, but a significant percentage were HR (ER/PR) positive. Moreover, we found an association between HR status and various clinicopathological features, indicating that HR status is a significant predictor of MBC prognosis.

Identification of Novel Molecular and Clinical Biomarkers of Survival in Glioblastoma Multiforme Patients: A Study Based on The Cancer Genome Atlas Data.

Glioblastoma multiforme (GBM) is the most prevalent type of brain tumour; although advancements in treatment have been made, the median survival time for GBM patients has persisted at 15 months. This study is aimed at investigating the genetic alterations and clinical features of GBM patients to find predictors of survival. GBM patients' methylation and gene expression data along with clinical information from TCGA were retrieved. The most overrepresented pathways were identified independently for each omics dataset. From the genes found in at least 30% of these pathways, one gene that was identified in both sets was further examined using the Kaplan-Meier method for survival analysis. Additionally, three groups of patients who started radio and chemotherapy at different times were identified, and the influence of these variations in treatment modality on patient survival was evaluated. Four pathways that seemed to negatively impact survival and two with the opposite effect were identified. The methylation status of PRKCB was highlighted as a potential novel biomarker for patient survival. The study also found that treatment with chemotherapy prior to radiotherapy can have a significant impact on patient survival, which could lead to improvements in clinical management and therapeutic approaches for GBM patients.

[Molecular pathological analysis through the ages]. / Molekularpathologische Untersuchungen im Wandel der Zeit.

BACKGROUND: Molecular pathological examinations of tumor samples encompass a wide range of diagnostic analyses. Especially in recent years, numerous new biomarkers have come to the forefront-the analysis of which is crucial for therapy decisions. OBJECTIVES: Within the field of molecular pathology, the demands of next generation sequencing (NGS)-based requirements have experienced massive growth in recent years. To meet this demand, methods are constantly being adapted and further developed. The following sections aim to illuminate how this trend arises and which analyses are gaining importance. METHODS: The article provides an overview of the essential nucleic acid-based analysis techniques in the field of massive parallel sequencing. Terms such as DNA- and RNA-based techniques, as well as the associated analysis methods, are described, particularly with regard to their use in routine molecular pathological diagnostics. RESULTS: The breadth of genomic sequencing has been steadily growing in recent years, particularly due to the increasing relevance of personalized medicine, along with the rising approvals of targeted therapeutics. This necessitates, among other things, the analysis of new biomarkers. The diagnostics as part of interdisciplinary molecular tumor boards (MTB) are now based on large gene panels (> 1 megabase). Furthermore, through the "Modellvorhaben Genomsequenzierung" § 64e, whole exome or whole genome sequencing has been made available for oncological patients. Given these developments, it is evident that future analyses will require the integration of additional omics fields, such as whole transcriptome analysis, epigenomics, and proteomics. CONCLUSION: The challenges of personalized medicine along with the necessity of simultaneously assessing numerous new biomarkers require the implementation and execution of new techniques in molecular pathology whose complexity is steadily increasing.

Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. METHODS: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. RESULTS: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. CONCLUSIONS: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities.

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

The correlation study between TOP2A gene expression in circulating tumor cells and chemotherapeutic drug resistance of patients with breast cancer.

BACKGROUND: Patients with breast cancer (BC) at advanced stages have poor outcomes because of high rate of recurrence and metastasis. Biomarkers for predicting prognosis remain to be explored. This study aimed to evaluate the relationships between circulating tumor cells (CTCs) and outcomes of BC patients. PATIENTS AND METHODS: A total of 50 female were enrolled in this study. Their diagnoses were determined by clinical characteristics, image data, and clinical pathology. CTC subtypes and TOP2A gene expression on CTCs were detected by CanPatrol™ technology and triple color in situ RNA hybridization (RNA-ISH), which divided into epithelial CTCs (eCTCs), mesenchymal CTCs (MCTCs), and hybrid CTCs (HCTCs) based on their surface markers. Hormone receptor, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) expression, was measured by immunohistochemistry (IHC) method before treatment. The risk factors for predicting recurrence and metastasis were calculated by COX risk regression model. The progression-free survival (PFS) of patients was determined using Kaplan-Meier survival curve. RESULTS: The patients with a large tumor size (≥ 3 cm) and advanced tumor node metastasis (TNM) stages had high total CTCs (TCTCs) (P < 0.05). These patients also had high TOP2A expression level. COX risk regression analysis indicated that TOP2A expression levels in TCTCs, ER + , HER-2 + , and TNM stages were critical risk factors for recurrence and metastasis of patients (P < 0.05). The PFS of patients with ≥ 5 TCTCs, ≥ 3 HCTCs, and positive TOP2A expression in ≥ 3 TCTCs was significantly longer than that in patient with < 5 TCTCs, < 3 HCTCs, and TOP2A expression in < 3 TCTCs (P < 0.05). In contrast, the PFS of patients with positive hormone receptors (ER + , PR + , HER-2 +) also was dramatically lived longer than that in patients with negative hormone receptor expression. CONCLUSIONS: High TCTC, HCTCs, and positive TOP2A gene expression on CTCs were critical biomarkers for predicting outcomes of BC patients. Positive hormone receptor expression in BC patients has significant favor PFS.

Contribution of tumour and immune cells to PD-L1 expression as a predictive biomarker in metastatic triple-negative breast cancer: exploratory analysis from KEYNOTE-119.

The efficacy of pembrolizumab monotherapy versus chemotherapy increased with increasing programmed death ligand 1 (PD-L1) expression, as quantified by combined positive score (CPS; PD-L1 expression on both tumour cells and immune cells) in patients with previously treated metastatic triple-negative breast cancer (mTNBC) in the phase 3 KEYNOTE-119 study. This exploratory analysis was conducted to determine whether the expression of PD-L1 on tumour cells contributes to the predictive value of PD-L1 CPS in mTNBC. PD-L1 expression in tumour samples was assessed using PD-L1 IHC 22C3 pharmDx and quantified using both CPS and tumour proportion score (TPS; PD-L1 expression on tumour cells alone). Calculated immune cell density (CID) was defined as CPS minus TPS. The ability of each scoring method (CPS, TPS, and CID) to predict clinical outcomes with pembrolizumab was evaluated. With pembrolizumab, the area under the receiver operating characteristic curve was 0.69 (95% CI = 0.58-0.80) for CPS, 0.55 (95% CI = 0.46-0.64) for TPS, and 0.67 (95% CI = 0.56-0.77) for CID. After correction for cutoff prevalence, CPS performed as well as, if not better than, CID with respect to predicting objective response rate, progression-free survival, and overall survival. Data from this exploratory analysis suggest that, although PD-L1 expression on immune cells alone is predictive of response to programmed death 1 blockade in mTNBC, adding tumour PD-L1 expression assessment (i.e. CPS, which combines immune cell and tumour cell PD-L1 expression) may improve prediction. PD-L1 CPS thus remains an effective and broadly applicable uniform scoring system for enriching response to programmed death 1 blockade with pembrolizumab in mTNBC as well as other tumour types.

IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability.

Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Early-stage patients have a 30-50% probability of metastatic recurrence after surgical treatment. Here, we propose a new computational framework, Interpretable Biological Pathway Graph Neural Networks (IBPGNET), based on pathway hierarchy relationships to predict LUAD recurrence and explore the internal regulatory mechanisms of LUAD. IBPGNET can integrate different omics data efficiently and provide global interpretability. In addition, our experimental results show that IBPGNET outperforms other classification methods in 5-fold cross-validation. IBPGNET identified PSMC1 and PSMD11 as genes associated with LUAD recurrence, and their expression levels were significantly higher in LUAD cells than in normal cells. The knockdown of PSMC1 and PSMD11 in LUAD cells increased their sensitivity to afatinib and decreased cell migration, invasion and proliferation. In addition, the cells showed significantly lower EGFR expression, indicating that PSMC1 and PSMD11 may mediate therapeutic sensitivity through EGFR expression.

DNA-based molecular classifiers for the profiling of gene expression signatures.

Although gene expression signatures offer tremendous potential in diseases diagnostic and prognostic, but massive gene expression signatures caused challenges for experimental detection and computational analysis in clinical setting. Here, we introduce a universal DNA-based molecular classifier for profiling gene expression signatures and generating immediate diagnostic outcomes. The molecular classifier begins with feature transformation, a modular and programmable strategy was used to capture relative relationships of low-concentration RNAs and convert them to general coding inputs. Then, competitive inhibition of the DNA catalytic reaction enables strict weight assignment for different inputs according to their importance, followed by summation, annihilation and reporting to accurately implement the mathematical model of the classifier. We validated the entire workflow by utilizing miRNA expression levels for the diagnosis of hepatocellular carcinoma (HCC) in clinical samples with an accuracy 85.7%. The results demonstrate the molecular classifier provides a universal solution to explore the correlation between gene expression patterns and disease diagnostics, monitoring, and prognosis, and supports personalized healthcare in primary care.

Immunoglobulin-like transcript 2 as an impaired anti-tumor cytotoxicity marker of natural killer cells in patients with hepatocellular carcinoma.

Introduction: Natural killer (NK) cells play a pivotal role in immune surveillance in the liver. We aimed to identify potential targets for NK cell-mediated immune intervention by revealing the functional molecules on NK cells in HCC patients. Methods: To evaluate the impact of aging on NK cell phenotypes, we examined NK cells from healthy volunteers (HVs) of various ages. Because ILT2 expression on CD56dim NK cells increased with increasing age, we enrolled age-matched HCC patients and HVs. We determined the NK cell phenotypes in blood mononuclear cells (PBMCs) and intrahepatic lymphocytes (IHLs) from cancerous and non-cancerous tissues. We evaluated cytotoxicity and antibody-dependent cellular cytotoxicity (ADCC) of NK cells in vitro. Results: ILT2-positive CD56dim NK cells in PBMCs were increased in HCC patients compared with HVs. In HCC patients, ILT2-positive CD56dim NK cells were increased in cancerous IHLs compared with non-cancerous IHLs and PBMCs. We examined the impact of macrophage migration inhibitory factor (MIF) on ILT2 expression in co-cultures of HCC cells and NK cells. The enhanced expression of ILT2 on CD56dim NK cells from HCC patients was inhibited by masking antibodies against MIF and CXCR4. ILT2-positive CD56dim NK cells exhibited lower capacities for cytotoxicity and ADCC than ILT2-negative cells, which were partially restored by ILT2 blockade. Conclusions: In HCC patients, ILT2 is a signature molecule for cancerous CD56dim NK cells with impaired cytolytic capacity. The MIF-CXCR4 interaction is associated with ILT2 induction on CD56dim NK cells and ILT2 serves as a target for functional NK cell restoration.

Microsatellite instability and mismatch repair protein deficiency: equal predictive markers?

Current clinical guidelines recommend mismatch repair (MMR) protein immunohistochemistry (IHC) or molecular microsatellite instability (MSI) tests as predictive markers of immunotherapies. Most of the pathological guidelines consider MMR protein IHC as the gold standard test to identify cancers with MMR deficiency and recommend molecular MSI tests only in special circumstances or to screen for Lynch syndrome. However, there are data in the literature which suggest that the two test types may not be equal. For example, molecular epidemiology studies reported different rates of deficient MMR (dMMR) and MSI in various cancer types. Additionally, direct comparisons of the two tests revealed relatively frequent discrepancies between MMR IHC and MSI tests, especially in non-colorectal and non-endometrial cancers and in cases with unusual dMMR phenotypes. There are also scattered clinical data showing that the efficacy of immune checkpoint inhibitors is different if the patient selection was based on dMMR versus MSI status of the cancers. All these observations question the current dogma that dMMR phenotype and genetic MSI status are equal predictive markers of the immunotherapies.