Prognostic Indicator Research Articles

The Utility of Lipidomic Analysis in Colorectal Cancer Diagnosis and Prognosis—A Systematic Review of Recent Literature

Colorectal cancer (CRC) is among the most prevalent and lethal malignancies. Lipidomic investigations have revealed numerous disruptions in lipid profiles across various cancers. Studies on CRC exhibit potential for identifying novel diagnostic or prognostic indicators through lipidomic signatures. This review examines recent literature regarding lipidomic markers for CRC. PubMed database was searched for eligible articles concerning lipidomic biomarkers of CRC. After selection, 36 articles were included in the review. Several studies endeavor to establish sets of lipid biomarkers that demonstrate promising potential to diagnose CRC based on blood samples. Phosphatidylcholine, phosphatidylethanolamine, ceramides, and triacylglycerols (TAGs) appear to offer the highest diagnostic accuracy. In tissues, lysophospholipids, ceramides, and TAGs were among the most altered lipids, while unsaturated fatty acids also emerged as potential biomarkers. In-depth analysis requires both cell culture and animal studies. CRC involves multiple lipid metabolism alterations. Although numerous lipid species have been suggested as potential diagnostic markers, the establishment of standardized methods and the conduct of large-scale studies are necessary to facilitate their clinical application.

The Prognostic Value of Advanced Lung Cancer Inflammation Index in Elderly Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

This study aimed to investigate the predictive value of advanced lung cancer inflammation index (ALI) for major adverse cardiovascular events (MACEs) in elderly patients with acute coronary syndrome (ACS).A total of 586 ACS patients undergoing percutaneous coronary intervention (PCI) over 65 years old between January 2017 and December 2018 were retrospectively collected. The patients were divided into two groups by the optimal cutoff value of ALI. Spearman rank correlation coefficient was used to evaluate the correlation between ALI and the Global Registry of Acute Coronary Events (GRACE). Time-dependent receiver operating characteristic (ROC) curves, Cox survival analysis, and Kaplan Meier curves were used to assess the predictive value of ALI for MACEs.Spearman's nonparametric test revealed a moderate correlation between ALI and the GRACE (r: -0.417, P < 0.001). Time-dependent ROC curves showed that the area under the curve for ALI was 0.751 (95% CI, 0.699-0.798) in predicting MACEs, higher than Geriatric Nutritional Risk Index (0.531, 95% CI 0.435-0.627) and Prognostic Nutritional Index (0.590, 95% CI 0.505 - 0.676), and for combined diagnostic models (ALI + GRACE) was 0.913, (95% CI 0.875 - 0.942, P < 0.001). Multivariate Cox analysis demonstrated that ALI (HR: 0.974, 95% CI: 0.952-0.996, P = 0.017) was an independent risk factor for MACEs. Kaplan Meier survival analysis showed that the cumulative incidence of MACEs was significantly higher in elderly ACS patients with lower ALI (log-rank test, P < 0.001).ALI could be a nutrition-inflammation indicator with independent predictive value for long-term MACEs of elderly ACS patients after PCI.

The clinical value of nutritional and inflammatory indicators in predicting pneumonia among patients with intracerebral hemorrhage

Immunosuppression and malnutrition play pivotal roles in the complications of intracerebral hemorrhage (ICH) and are intricately linked to the development of stroke-associated pneumonia (SAP). Inflammatory markers, including NLR (neutrophil-to-lymphocyte ratio), SII (systemic immune inflammation index), SIRI (systemic inflammatory response index), and SIS (systemic inflammation score), along with nutritional indexes such as CONUT (controlling nutritional status) and PNI (prognostic nutritional index), are crucial indicators influencing the inflammatory state following ICH. In this study, our objective was to compare the predictive efficacy of inflammatory and nutritional indices for SAP in ICH patients, aiming to determine and explore their clinical utility in early pneumonia detection. Patients with severe ICH requiring ICU admission were screened from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The outcomes included the occurrence of SAP and in-hospital death. Receiver operating characteristic (ROC) analysis, multivariate logistic regression, smooth curve analysis, and stratified analysis were employed to investigate the relationship between the CONUT index and the clinical outcomes of patients with severe ICH. A total of 348 patients were enrolled in the study. The incidence of SAP was 21.3%, and the in-hospital mortality rate was 17.0%. Among these indicators, multiple regression analysis revealed that CONUT, PNI, and SIRI were independently associated with SAP. Further ROC curve analysis demonstrated that CONUT (AUC 0.6743, 95% CI 0.6079–0.7408) exhibited the most robust predictive ability for SAP in patients with ICH. Threshold analysis revealed that when CONUT < 6, an increase of 1 point in CONUT was associated with a 1.39 times higher risk of SAP. Similarly, our findings indicate that CONUT has the potential to predict the prognosis of patients with ICH. Among the inflammatory and nutritional markers, CONUT stands out as the most reliable predictor of SAP in patients with ICH. Additionally, it proves to be a valuable indicator for assessing the prognosis of patients with ICH.

Thromboinflammation in COVID-19: Unraveling the interplay of coagulation and inflammation.

The coronavirus disease 2019 (COVID-19) pandemic has not only challenged global health systems but also spurred intense scientific inquiry into its pathophysiology. Among the multifaceted aspects of the disease, coagulation abnormalities have emerged as a significant contributor to morbidity and mortality. From endothelial dysfunction to dysregulated immune responses, various factors contribute to the hypercoagulable state seen in severe COVID-19 cases. The dysregulation of coagulation in COVID-19 extends beyond traditional thromboembolic events, encompassing a spectrum of abnormalities ranging from microvascular thrombosis to disseminated intravascular coagulation (DIC). Endothelial injury induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection triggers a cascade of events involving platelet activation, coagulation factor consumption, and fibrinolysis impairment. Moreover, the virus direct effects on immune cells and the cytokine storm further exacerbate the prothrombotic milieu. Unraveling this intricate web of interactions between viral pathogenesis and host responses is essential for elucidating novel therapeutic targets and refining existing management strategies for COVID-19-associated coagulopathy. In the quest to unravel the complex interplay between coagulation and COVID-19, numerous clinical and laboratory studies have yielded invaluable insights into potential biomarkers, prognostic indicators, and therapeutic avenues. Anticoagulation therapy has emerged as a cornerstone in the management of severe COVID-19, although optimal dosing regimens and patient selection criteria remain subjects of ongoing investigation. Additionally, innovative approaches such as targeting specific components of the coagulation cascade or modulating endothelial function hold promise for future therapeutic development.

Construction of prognostic markers for pancreatic adenocarcinoma based on mitochondrial fusion-related genes.

Early detection of pancreatic adenocarcinoma (PAAD) remains a pressing clinical problem. Information on the clinical prognostic value of mitochondrial fusion-related genes in PAAD remains limited. In this study, we investigated mitochondrial fusion-related genes of PAAD to establish an optimal signature plate for the early diagnosis and prognosis of PAAD. The cancer genome atlas database was used to integrate the Fragments Per Kilobase Million data and related clinical data for patients with PAAD. Least absolute shrinkage and selection operator regression, cox regression, operating characteristic curves, and cBioPortal database was used to evaluate model performance, assess the prognostic ability and sensitivity. The levels of immune infiltration were compared by CIBERSORT, QUANTISEQ, and EPIC. Chemotherapy sensitivity between the different risk groups was compared by the Genomics of Drug Sensitivity in Cancer database and the "pRRophetic" R package. At last, a total of 4 genes were enrolled in multivariate Cox regression analysis. The risk-predictive signature was constructed as: (0.5438 × BAK1) + (-1.0259 × MIGA2) + (1.1140 × PARL) + (-0.4300 × PLD6). The area under curve of these 4 genes was 0.89. Cox regression analyses indicates the signature was an independent prognostic indicator (P < .001, hazard ratio [HR] = 1.870, 95% CI = 1.568-2.232). Different levels of immune cell infiltration in the 2 risk groups were observed using the 3 algorithms, with tumor mutation load (P = .0063), tumor microenvironment score (P = .01), and Tumor Immune Dysfunction and Exclusion score (P = .0012). The chemotherapeutic sensitivity analysis also revealed that the half-maximal inhibitory concentration of 5-fluorouracil (P = .0127), cisplatin (P = .0099), docetaxel (P < .0001), gemcitabine (P = .0047), and pacilataxel (P < .0001) were lower in the high-risk groups, indicating that the high-risk group patients had a greater sensitivity to chemotherapy. In conclude, we established a gene signature plate comprised of 4 mitochondrial fusion related genes to facilitate early diagnosis and prognostic prediction of PAAD.

Identification of HOXC Gene Family as Prognostic and Immune-Related Biomarkers in Breast Cancer Through mRNA Transcriptional Profile and Experimental Validation.

Breast cancer (BC) is the most common malignancy in women worldwide, and more effective biomarkers are urgently needed for the prevention and treatment of BC. Our study aimed to investigate the role of the HOXC gene family (HOXCs) and its relationship with the immune response in BC. The differential expression of HOXCs and its clinical prognostic significance in BC were explored using bioinformatics analysis, and the cBioPortal database was used to evaluate the genetic mutation profile of the HOXCs in BC. The results indicated that the expression levels of HOXC4, 10, 11, 12, and 13 were significantly increased in BC tissues compared with the normal tissues, and expressions of these genes were closely associated with BC stage, among them, high expression levels of HOXC10 and HOXC13 predicted poor outcome in BC patients. In addition, to elucidate the essential role of HOXCs in the tumor microenvironment and immunotherapeutic response of BC, the impact of HOXCs on the regulation of immune infiltration in BC was comprehensively assessed. The result showed thatHOXC10 and HOXC13 expressions were significantly positively linked with the infiltration levels of CD8+T cell and M1 macrophage, while they werenegatively related to Mast and Natural killer cells, suggesting the important influence of HOXCs on regulating tumor immunity in BC patients. Lastly, the RT-qPCR assay was employed to validate HOXCs expression in samples of BC patients. In conclusion, HOXCs may be a promising prognostic indicator and couldregulate the immune infiltration in BC patients, thus being apromising targeted immunotherapy for BC.

Three biomarkers (HER2, PD-L1, and microsatellite status) in a large cohort of metastatic gastroesophageal adenocarcinomas: The MD Anderson Cancer Center experience.

Human epidermal growth factor receptor-2 (HER2), programmed death-ligand 1 (PD-L1), and microsatellite (MS) status are well-established biomarkers in gastroesophageal adenocarcinomas (GEAs). However, it is unclear how the combination of these biomarkers is associated with clinicopathological factors and prognosis. This retrospective study included baseline metastatic GEA patients who were tested for all three biomarkers (HER2, PD-L1, and MS status) at the MD Anderson Cancer Center between 2012 and 2022. Stratification was performed according to the combination of biomarker profiles: triple negative (TN), single positive (SP), and multiple positive (MP). Comparative analyses of clinicopathological factors and survival using combinations of biomarkers were performed. Among the 698 GEA patients analyzed, 251 (36.0%) were classified as TN, 334 (47.9%) as SP, and 113 (16.1%) as MP. The MP group showed a significant association with tumors located in the esophagus (p < .001), well to moderate differentiation (p < .001), and the absence of signet ring cells (p < .001). In the survival analysis, MP group had a significantly longer overall survival (OS) compared to the other groups (MP vs. TN, p < .001 and MP vs. SP, p < .001). Multivariate Cox regression analysis revealed that MP serves as an independent positive prognostic indicator for OS (hazard ratio = 0.63, p < .01). Our findings indicate that MP biomarkers are associated with a favorable prognosis in metastatic GEA. These results are reflective of clinical practice and offer valuable insights into how therapeutics and future biomarkers could influence therapy/prognosis.

Metabolism score and machine learning models for the prediction of esophageal squamous cell carcinoma progression.

The incomplete prediction of prognosis in esophageal squamous cell carcinoma (ESCC) patients is attributed to various therapeutic interventions and complex prognostic factors. Consequently, there is a pressing demand for enhanced predictive biomarkers that can facilitate clinical management and treatment decisions. This study recruited 491 ESCC patients who underwent surgical treatment at Huashan Hospital, Fudan University. We incorporated 14 blood metabolic indicators and identified independent prognostic indicators for overall survival through univariate and multivariate analyses. Subsequently, a metabolism score formula was established based on the biochemical markers. We constructed a nomogram and machine learning models utilizing the metabolism score and clinically significant prognostic features, followed by an evaluation of their predictive accuracy and performance. We identified alkaline phosphatase, free fatty acids, homocysteine, lactate dehydrogenase, and triglycerides as independent prognostic indicators for ESCC. Subsequently, based on these five indicators, we established a metabolism score that serves as an independent prognostic factor in ESCC patients. By utilizing this metabolism score in conjunction with clinical features, a nomogram can precisely predict the prognosis of ESCC patients, achieving an area under the curve (AUC) of 0.89. The random forest (RF) model showed superior predictive ability (AUC = 0.90, accuracy = 86%, Matthews correlation coefficient = 0.55). Finally, we used an RF model with optimal performance to establish an online predictive tool. The metabolism score developed in this study serves as an independent prognostic indicator for ESCC patients.

Plasma SCUBE2 as a novel biomarker associates with survival outcomes in patients with sepsis-associated acute kidney injury

BackgroundThe adverse effects of sepsis-associated acute kidney injury (SA-AKI) highlight the need for new biomarkers. Signal Peptide-Complement C1r/C1s, Uegf, Bmp1-Epidermal Growth Factor-like Domain-Containing Protein 2 (SCUBE2), important for angiogenesis and endothelial integrity, has been linked to increased mortality in models of lipopolysaccharide-induced lung injury. This research aimed to assess the utility of plasma SCUBE2 levels as a prognostic indicator for SA-AKI in intensive care unit (ICU) patients. MethodsBetween January 2020 and December 2022, our study enrolled ICU patients diagnosed with stage 3 SA-AKI. We collected demographic information, illness severity indices, and laboratory data, including plasma SCUBE2 and sepsis-triggered cytokine levels. We employed receiver operating characteristic curves and DeLong tests to assess the predictive accuracy for survival, Kaplan–Meier curves to evaluate the relative risk of death, and multivariate logistic regression to identify independent mortality predictors. ResultsAmong the total of 200 participants, the survivors had significantly higher plasma SCUBE2 levels (115.9 ng/mL) compared to those who died (35.6 ng/mL). SCUBE2 levels showed a positive correlation with the anti-inflammatory cytokine IL-10 and a negative correlation with the APACHE II score, SOFA score, C-reactive protein, and monocyte chemoattractant protein-1. Multivariate analysis revealed that elevated SCUBE2 and IL-10 levels were independently protective against mortality, and associated with the most favorable 30-day survival outcomes. ConclusionsIn ICU patients with stage 3 SA-AKI, lower plasma levels of SCUBE2 were correlated with elevated pro-inflammatory factors, which impacted survival outcomes. This suggests that SCUBE2 could be a potential biomarker for predicting prognosis in patients with SA-AKI.

The Influence of Inflammatory and Nutritional Status on the Long-Term Outcomes in Advanced Stage Ovarian Cancer

Background: Despite improving surgical techniques and achieving more often complete debulking procedures, certain patients with advanced-stage ovarian cancer still have a very poor prognosis. The aim of the current paper is to investigate whether inflammatory and nutritional status can predict the long-term outcomes of ovarian cancer patients. Methods: A retrospective analysis of 57 cases diagnosed with advanced-stage ovarian cancer submitted to surgery as first intent therapy was carried out. In all cases, the preoperative status was determined by calculating the CRP/albumin ratio, as well as the Glasgow score, the modified Glasgow score and the prognostic nutritional index. Results: Patients presenting higher values of the CRP/albumin ratio, with a higher Glasgow score, modified Glasgow score and prognostic nutritional index (PNI), were more frequently associated with incomplete debulking surgery, a higher peritoneal carcinomatosis index and poorer overall survival (20 months versus 9 months for the CRP/albumin ratio p = 0.011, 42 versus 27 versus 12 months for the Glasgow score p = 0.042, 50 versus 19 versus 12 months for the modified Glasgow score, p = 0.001, and 54 months versus 21 months, p = 0.011 for the prognostic nutritional index). Conclusions: A strong relationship between the nutritional and inflammatory status in advanced-stage ovarian cancer seems to exist.

Treatment, Prognostic Markers, and Survival in Thymic Neuroendocrine Tumors, with Special Reference to Temozolomide-Based Chemotherapy

Background: Thymic neuroendocrine tumors (Th-NETs) are rare and aggressive, with a scarcity of research on predicting patient prognosis. Our study aimed to assess the impact of prognostic markers and temozolomide (TMZ)-based chemotherapy on survival in Th-NETs. Methods: We retrospectively reviewed the medical records of patients diagnosed with Th-NETs between 2013 and 2023 at our institution. We collected clinicopathological data, including tumor pathological grading, staging, serum concentrations of neuron-specific enolase (NSE) and pro-gastrin-releasing peptide, levels of inflammatory factors, and expression of oxygen 6-methylguanine-DNA methyltransferase (MGMT). Treatment details (such as surgery and chemotherapy) and survival outcomes were also documented. Results: A total of 32 patients were included in our study after excluding those without complete available information. The median progression-free survival (PFS) was 12.5 months (95%CI, 8–16 months) for 19 patients who received TMZ-based chemotherapy. Twenty-one patients underwent surgery as the primary treatment, demonstrating a median disease-free survival (DFS) of 51.0 months. The inflammatory factor neutrophil-to-lymphocyte ratio (NLR) was an independent prognostic indicator of DFS in postoperative patients and PFS in TMZ-treated patients. The overall 3-, 5-, and 10-year survival rates were 86.6%, 69.5%, and 33.8%, respectively. Ki67 level exceeding 10% (p = 0.048) and absence of surgical resection (p = 0.003) were significantly associated with worse overall survival (OS). Conclusion: Surgical treatment was currently the primary method for treating Th-NETs, and postoperative adjuvant therapy was an essential consideration for specific patient cohorts. Despite widespread positive MGMT expression, TMZ-based chemotherapy showed promise. Some potential prognostic biomarkers such as NLR and NSE need more attention.

Normalized lactate load as an independent prognostic indicator in patients with cardiogenic shock

BackgroundEarly prognosis evaluation is crucial for decision-making in cardiogenic shock (CS) patients. Dynamic lactate assessment, for example, normalized lactate load, has been a better prognosis predictor than single lactate value in septic shock. Our objective was to investigate the correlation between normalized lactate load and in-hospital mortality in patients with CS.MethodsData were extracted from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The calculation of lactate load involved the determination of the cumulative area under the lactate curve, while normalized lactate load was computed by dividing the lactate load by the corresponding period. Receiver Operating Characteristic (ROC) curves were constructed, and the evaluation of areas under the curves (AUC) for various parameters was performed using the DeLong test.ResultsOur study involved a cohort of 1932 CS patients, with 687 individuals (36.1%) experiencing mortality during their hospitalization. The AUC for normalized lactate load demonstrated significant superiority compared to the first lactate (0.675 vs. 0.646, P < 0.001), maximum lactate (0.675 vs. 0.651, P < 0.001), and mean lactate (0.675 vs. 0.669, P = 0.003). Notably, the AUC for normalized lactate load showed comparability to that of the Sequential Organ Failure Assessment (SOFA) score (0.675 vs. 0.695, P = 0.175).ConclusionThe normalized lactate load was an independently associated with the in-hospital mortality among CS patients.

Transarterial chemoembolization for renal cell carcinoma patients with liver metastases in the era of immunotherapy: A case series

Treatment for renal cell carcinoma (RCC) has changed rapidly in the past decade with the widespread implementation of immune checkpoint inhibitors (ICIs) as first-line therapy in metastatic disease. The presence of liver metastases is a poor prognostic indicator but also has the potential to be a target for localized therapy. However, there is limited knowledge on the dynamics and long-term effects of combining liver-directed transarterial chemoembolization (TACE) with ICI therapy. We identified four patients with metastatic RCC (mRCC) and liver metastases who were treated concurrently with ICIs and TACE to metastatic liver lesions from our institutional database. We assessed treatment radiological responses and toxicity in this cohort. Liver-directed TACE with concurrent ICI was associated with radiological response or stabilization in all the liver lesions in the four patients in this cohort with a median time to locoregional liver metastasis progression-free survival of 8.3 months (range 6.0–11.1). The concurrent administration of ICI therapy and TACE to liver lesions was well tolerated with no new safety signals and no immune-related toxicities. Combining TACE with ICI in patients with mRCC showed promising response with limited toxicity. Future studies are warranted to clarify treatment timing and validate benefits.

A Prediction Rule for the Dystonic Spread of Blepharospasm: A 4-Year Prospective Cohort Study.

Blepharospasm (BSP), focal dystonia with the highest risk of spread, lacks clear understanding of early spreading risk factors and objective prognostic indicators. We aimed to identify these risk factors through clinical and electrophysiological assessments, and to establish a predictive model for dystonic spread in BSP. We prospectively followed BSP patients for 4 years, collecting data on dystonic spread, and conducting electrophysiological evaluations. The blink reflex, masseter inhibitory reflex, and trigeminal somatosensory evoked potential were assessed. Univariable and multivariable Cox proportional hazard regression models were used to assess clinical characteristics associated with BSP dystonic spread. A predictive model was constructed using a nomogram, and performance of the model was evaluated using the area under the receiver operating characteristic curve. A total of 136 enrolled participants (mean age 56.34 years) completed a 4-year follow-up. Among them, 62 patients (45.6%) showed spread to other body regions. Multivariable Cox regression analysis showed that a high Hamilton Anxiety Scale score (hazard ratio 1.19, 95% confidence interval 1.13-1.25, p < 0.001), prolonged trigeminal somatosensory evoked potential mandibular branch P1-N2 peak interval (hazard ratio 1.11, 95% confidence interval 1.02-1.21, p = 0.017), and elevated trigeminal somatosensory evoked potential mandibular branch P1-N2 peak amplitude (hazard ratio 1.26, 95% confidence interval 1.12-1.41, p < 0.001) were independent risk factors for BSP dystonic spread within 4 years. Combining these factors, the predictive models demonstrated excellent discriminative ability, with the receiver operating characteristic curve score being 0.797, 0.790, 0.847, and 0.820 at 1, 2, 3 and 4 years after enrollment, respectively. We established a predictive model with significant value for anticipating dystonic spread in BSP, offering crucial evidence. These findings contribute essential insights into the early clinical identification of the development and evolution of BSP diseases. ANN NEUROL 2024.

Hemoglobin levels and cognitive trajectory: unveiling prognostic insights in post-stroke geriatric cohort

Evidence is scarce regarding the association between anemia and alterations in cognitive level among hospitalized older patients. We aimed to evaluate the associations between baseline hemoglobin (Hb) levels and changes in cognitive level in patients undergoing rehabilitation after stroke. A retrospective cohort study was conducted, encompassing consecutively hospitalized post-stroke patients. Data on serum Hb levels were extracted from medical records, specifically tests conducted within 24 hours of admission. Primary outcomes included discharge scores for cognitive function assessed by the cognitive domain of the Functional Independence Measure (FIM-cognition) and the corresponding change in FIM-cognition during hospitalization. Another outcome measure was the length of hospital stay. Multivariate linear regression analyses were employed to assess the association between Hb levels at admission and the designated outcomes, adjusting for potential confounding factors. Data from 955 patients (mean age 73.2 years; 53.6% men) were included in the analysis. The median Hb level at admission was 13.3 [11.9, 14.5] g/dL. After fully adjusting for confounding factors, the baseline Hb level was significantly and positively associated with FIM-cognition at discharge (β = 0.045, p = 0.025) and its gain (β = 0.073, p = 0.025). Further, the baseline Hb level was independently and negatively associated with length of hospital stay (β = -0.013, p = 0.026). Elevated baseline Hb levels are correlated with preserved cognitive level and shorter hospital stays in post-stroke patients. Evaluating anemia at the outset serves as a crucial prognostic indicator.

A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma

BackgroundCancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role in tumor microenvironment shaping and immunotherapy response. Current prognostic indexes are insufficient to accurately assess immunotherapy response in patients with head and neck squamous cell carcinoma (HNSCC). This study aimed to develop a CCCT-related gene prognostic index (CCRGPI) for assessing the prognosis and response to immune checkpoint inhibitor (ICI) therapy of HNSCC patients.MethodsTwo cellular models, the fibroblast-cancer cell indirect coculture (FCICC) model, and the fibroblast-cancer cell organoid (FC-organoid) model, were constructed to visualize the crosstalk between fibroblasts and cancer cells. Based on a HNSCC scRNA-seq dataset, the R package CellChat was used to perform cell communication analysis to identify gene pairs involved in CCCT. Least absolute shrinkage and selection operator (LASSO) regression was then applied to further refine the selection of these gene pairs. The selected gene pairs were subsequently subjected to stepwise regression to develop CCRGPI. We further performed a comprehensive analysis to determine the molecular and immune characteristics, and prognosis associated with ICI therapy in different CCRGPI subgroups. Finally, the connectivity map (CMap) analysis and molecular docking were used to screen potential therapeutic drugs.ResultsFCICC and FC-organoid models showed that cancer cells promoted the activation of fibroblasts into CAFs, that CAFs enhanced the invasion of cancer cells, and that CCCT was somewhat heterogeneous. The CCRGPI was developed based on 4 gene pairs: IGF1-IGF1R, LGALS9-CD44, SEMA5A-PLXNA1, and TNXB-SDC1. Furthermore, a high CCRGPI score was identified as an adverse prognostic factor for overall survival (OS). Additionally, a high CCRGPI was positively correlated with the activation of the P53 pathway, a high TP53 mutation rate, and decreased benefit from ICI therapy but was inversely associated with the abundance of various immune cells, such as CD4+ T cells, CD8+ T cells, and B cells. Moreover, Ganetespib was identified as a potential drug for HNSCC combination therapy.ConclusionsThe CCRGPI is reliable for predicting the prognosis and immunotherapy response of HSNCC patients and may be useful for guiding the individualized treatment of HNSCC patients.

A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma

BackgroundCancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role in tumor microenvironment shaping and immunotherapy response. Current prognostic indexes are insufficient to accurately assess immunotherapy response in patients with head and neck squamous cell carcinoma (HNSCC). This study aimed to develop a CCCT-related gene prognostic index (CCRGPI) for assessing the prognosis and response to immune checkpoint inhibitor (ICI) therapy of HNSCC patients.MethodsTwo cellular models, the fibroblast-cancer cell indirect coculture (FCICC) model, and the fibroblast-cancer cell organoid (FC-organoid) model, were constructed to visualize the crosstalk between fibroblasts and cancer cells. Based on a HNSCC scRNA-seq dataset, the R package CellChat was used to perform cell communication analysis to identify gene pairs involved in CCCT. Least absolute shrinkage and selection operator (LASSO) regression was then applied to further refine the selection of these gene pairs. The selected gene pairs were subsequently subjected to stepwise regression to develop CCRGPI. We further performed a comprehensive analysis to determine the molecular and immune characteristics, and prognosis associated with ICI therapy in different CCRGPI subgroups. Finally, the connectivity map (CMap) analysis and molecular docking were used to screen potential therapeutic drugs.ResultsFCICC and FC-organoid models showed that cancer cells promoted the activation of fibroblasts into CAFs, that CAFs enhanced the invasion of cancer cells, and that CCCT was somewhat heterogeneous. The CCRGPI was developed based on 4 gene pairs: IGF1-IGF1R, LGALS9-CD44, SEMA5A-PLXNA1, and TNXB-SDC1. Furthermore, a high CCRGPI score was identified as an adverse prognostic factor for overall survival (OS). Additionally, a high CCRGPI was positively correlated with the activation of the P53 pathway, a high TP53 mutation rate, and decreased benefit from ICI therapy but was inversely associated with the abundance of various immune cells, such as CD4+ T cells, CD8+ T cells, and B cells. Moreover, Ganetespib was identified as a potential drug for HNSCC combination therapy.ConclusionsThe CCRGPI is reliable for predicting the prognosis and immunotherapy response of HSNCC patients and may be useful for guiding the individualized treatment of HNSCC patients.

Cardiac power output ratio: Novel survival predictor after percutaneous ventricular assist device in cardiogenic shock.

Currently, there is limited data on prognostic indicators after insertion of percutaneous ventricular assist device (PVAD) in the treatment of cardiogenic shock (CS). This study evaluated the prognostic role of cardiac power output (CPO) ratio, defined as CPO at 24h divided by early CPO (30min to 2h), in CS patients after PVAD. Consecutive CS patients from the QEH-PVAD Registry were followed up for survival at 90days after PVAD. Among 121 consecutive patients, 98 underwent right heart catheterization after PVAD, with CPO ratio available in 68 patients. The CPO ratio and 24-h CPO, but not the early CPO post PVAD, were significantly associated with 90-day survival, with corresponding area under curve in ROC analysis of 0.816, 0.740, and 0.469, respectively. In multivariate analysis, only the CPO ratio and lactate level at 24h remained as independent survival predictors. The CPO ratio was not associated with age, sex, and body size. Patients with lower CPO ratio had significantly lower coronary perfusion pressure, worse right heart indices, and higher pulmonary vascular resistance. A lower CPO ratio was also significantly associated with mechanical ventilation and higher creatine kinase levels in myocardial infarction patients. In post-PVAD patients, the CPO ratio outperformed the absolute CPO values and other haemodynamic metrics in predicting survival at 90days. Such a proportional change of CPO over time, likely reflecting native heart function recovery, may help to guide management of CS patients post-PVAD.

Cancer histology in metastatic lymph node predicts prognosis in patients with node-positive stage IV colorectal cancer.

Appropriate prognostic indicators are required for patients with stage IV colorectal cancer (CRC). Lymph node metastasis mainly involves four histological types of CRC. Some metastatic lymph nodes (mLNs) showing cribriform carcinoma are associated with distant metastasis in patients with node-positive CRC and are correlated with recurrence and survival in stage III disease. However, the significance of mLN histology in the prognosis of patients with node-positive stage IV disease remains unclear. We enrolled 449 consecutive patients with CRC who underwent primary tumor resection with lymph node dissection between January 2011 and November 2018. This study included 88 patients with node-positive stage IV CRC and synchronous or metachronous distant metastases. We retrospectively investigated the association between cancer histology in the mLNs based on our classification and cancer-specific survival (CSS) in patients with node-positive stage IV CRC. Kaplan-Meier analysis showed that CSS was better in patients with CRC and all the mLNs showing tubular-type carcinoma. In contrast, patients with at least some mLNs showing poorly differentiated-type carcinoma had poor prognosis. Multivariate analysis showed that "all mLNs showing tubular-type carcinoma" was an independent good prognostic factor for CSS in patients with node-positive stage IV CRC. In addition, "at least some mLNs showing poorly differentiated-type carcinoma" was an independent poor prognostic factor for CSS in patients with node-positive stage IV disease. The histological type of the mLN may indicate a better or poor prognosis for patients with stage IV CRC.

Biomarkers and Related Factors for the Diagnosis, Risk of Coronary Artery Lesions, and Resistance to Intravenous Immunoglobulin in Kawasaki Disease: An Umbrella Review of Meta-Analyses.

Kawasaki disease (KD) is a self-limited febrile disease predominantly affecting infants and children under 5 years old. Coronary artery lesions (CAL) are a prevalent complication, highlighting the necessity for swift diagnosis and treatment. A comprehensive review of biomarkers applicable for the diagnosis and treatment of Kawasaki disease (KD) in clinical settings is imperative. To provide a comprehensive review and analysis of biomarkers for diagnosis of KD, incidence of CAL, and intravenous immunoglobulin (IVIG) resistance. The data included in our study were sourced from searches conducted in PubMed/MEDLINE, Embase, EBSCO, and Google Scholar until March 15, 2024. Studies investigating the association with KD or evaluating diagnostic value were included in our study. Eligibility was independently assessed by two authors, with conflicts resolved through discussion. Data extraction was performed by 2 independent authors, following Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guideline. Data were pooled using a random-effects model. We assess biomarkers relevant to KD, categorizing them into three groups: diagnostic, associated with CAL incidence, and linked to IVIG resistance. For studies focusing solely on association, we present standardized mean differences (SMD). For those reporting sensitivity and specificity as diagnostic measures, we calculate the diagnostic odds ratio (DOR) to compare their efficacy. We identified 14 meta-analyses on biomarkers related to KD. 11 biomarkers exhibited diagnostic value for KD, while 21 were associated with its progression. Four biomarkers, including non-codingRNAs (DOR, 19.35 [95% CI, 13.58-27.56]), Serumferritin (DOR, 24.90 [11.67-53.12]), NterminalproBNP (DOR, 21.03 [9.03-49.00]), and microRNAs (DOR, 45.28 [6.30-325.52]), have significant diagnostic value for the diagnosis of KD. Seven biomarkers showed significant association with the incidence of CAL. Twenty biomarkers were for the prediction of IVIG resistance, including prognostic nutritional index (DOR, 7.72 [95% CI, 2.37-25.09]), non-codingRNAs (DOR, 14.63 [3.24-66.14]), neutrophil to lymphocyte ratio (DOR, 6.62 [4.05-10.81]), platelet to lymphocyte ratio (DOR, 3.30 [2.10-5.19]), and Creactive protein (DOR, 6.58 [3.69-11.74]). Based on the evidence, we have proposed various biomarkers associated with KD. Our aim is for these biomarkers to have wide applicability in both diagnostic and therapeutic settings.