Prognosis Of Patients Research Articles

MGMT protein expression is a reliable predictive biomarker for temozolomide-containing chemotherapy in osteosarcoma.

The prognosis of patients with osteosarcoma who experience recurrence or progression (R/P) is extremely poor, and more effective and less toxic therapies are needed. In the current study, the clinical data of osteosarcoma patients who experienced R/P were retrospectively analyzed to verify the reliability of O-6-methylguanine-DNA methyltransferase (MGMT) protein expression or MGMT promoter methylation for predicting the response to off-label temozolomide (TMZ)-containing chemotherapy. Of the 30 evaluable patients, 9 (30%) showed no/low MGMT protein expression, whereas all 16 evaluable patients had unmethylated MGMT promoter irrespective of MGMT protein expression levels. Twenty-three patients received TMZ-containing chemotherapy for measurable lesions (n = 14) or as adjuvant therapy following resection of recurrent lesions (n = 9). Among 14 patients with radiologically measurable lesions, the objective response rate was higher in the MGMT no/low-expression group (50.0%) than in the MGMT intermediate/high-expression group with borderline significance (0%, p = 0.066). The 6-month progression-free survival (PFS) rate in patients with radiologically measurable lesions was significantly higher in the MGMT no/low-expression group (50.0%) than in the MGMT intermediate/high-expression group (0%, p = 0.036). In the multivariate analysis of the 23 patients receiving TMZ-containing chemotherapy, MGMT expression and disease status before TMZ-containing chemotherapy were significantly associated with PFS. No severe adverse effects were observed during TMZ-containing chemotherapy. MGMT protein expression, but not MGMT promoter methylation, could predict a favorable outcome in patients receiving TMZ-containing chemotherapy.

Chronic kidney disease and chronic heart failure: impact on prognosis and choice of pathogenetic therapy

To evaluate the impact of a decrease in glomerular filtration rate (GFR) on the prognosis of patients with chronic heart failure (CHF), to analyze real clinical practice regarding the frequency of prescribing pathogenetic therapy for CHF, achieving target dosages depending on the gradation of GFR in patients included in the CHF Register of the Tyumen region. The analysis included medical data of 4077 patients (1662 men and 2415 women) with NYHA class I-IV CHF who underwent examination and treatment in medical organizations of the Tyumen region for the period from January 2020 to May 2023. Criteria for inclusion in the register: proven heart failure. Chronic kidney disease (CKD) was assessed by GFR calculated using the CKD-EPI formula (ml/min/1.73 m2). The primary end point was defined as death from all causes. GFR<60 ml/min/1.73 m2 was recorded in 34.6% of patients, more common in women (40.2 and 26.6%, respectively; p<0.001). When dividing patients into phenotypes according to LVEF, no statistically significant differences were found in the distribution of patients according to GFR. In patients with HFrEF and HFpEF GFR<45 ml/min/1.73 m2 was associated with an increased risk of meeting the endpoint. Analysis of prescribed pathogenetic therapy showed that in patients with HFrEF, the frequency of prescription of ACE inhibitors, â-blockers and MRA decreased (p=0.023, 006 and 0.01, respectively), and ARNI, on the contrary, increased with a decrease in GFR (p=0.026). In patients with HFpEF, a similar trend towards a decrease in the frequency of prescription of ACEIs and MCBs with a decrease in GFR (p<0.001) remained, but it was compensated by an inversely proportional increase in the frequency of prescription of ARBs (p<0.001). 100% of the target dosage is achieved in more than 90% of patients taking MRA across the entire LVEF range. While for â-blockers and ARNI/ACE/ARB the percentage of patients receiving the full therapeutic dosage of drugs is significantly lower. When analyzing target dosages of pathogenetic drugs, gradations of achieved doses were distributed evenly throughout the entire range of GFR. GFR<60 ml/min/1.73 m2 occurs in every 3 patients with CHF across the entire range of LVEF. A decrease in GFR worsens the prognosis of patients with both HFrEF and HFpEF, increasing in direct proportion with the severity of the stage of CKD. Inclusion of patients in the monitoring program within the framework of the CHF service allows the treatment to be significantly brought closer to optimal drug therapy, at the same time, certain efforts are required to overcome difficulties with titration to target dosages.

Expression of TGF-β/Smad pathway-related indices in patients with isolated iliac artery aneurysms complicated with iliac arteriovenous fistula and their relationship with prognosis

ABSTRACT Objective This study investigated the expression of TGF-β/Smad pathway-related indices in patients with isolated iliac artery aneurysms (IIAA) complicated with iliac arteriovenous fistula (IAVF) and their relationship with prognosis. Methods From January 2016 to June 2022, 83 patients with IIAA complicated with IAVF (Study group) and 54 patients with IIAA not complicated with IAVF (control group) were studied. The related indices of TGF-β/Smad pathway were evaluated, and the effects of each index on the formation of IAVF were analyzed. The patients were divided into the survival group (64 cases) and death group (19 cases), and the prognostic value of indices in combination was analyzed. Results TGF-β, p-Smad2, p-Smad3, p-JNK, and p-ERK in the study group were higher than those in the control group. Abnormal increase of pSmad3 expression was a risk factor for IAVF formation in patients with IIAA. TGF-β level in the death group was higher than that in the survival group, and p-Smad3 and p-JNK proteins were higher than those in the survival group. The AUC value of indices in the TGF-β/Smad pathway in combination was greater than that of each index alone. Abnormal increased expression of pSmad3 was a risk factor for prognosis of patients with IIAA complicated with IAVF. Conclusion The abnormal increase of TGF-β/Smad pathway-related indices is related to poor prognosis of patients with IIAA complicated with IAVF, and the combined detection of all indices has a predictive value for patients’ prognosis.

Research Progress on Application of Time Nursing in Stroke Patients

Stroke is a common cerebrovascular disease with high mortality and disability in clinic, it is a "killer" that endangers human health and imposes a heavy burden on patients families and society. Stroke is one of the chronic diseases. The rehabilitation of patients is a gradual and long process. As an important part of the rehabilitation of stroke patients, the effectiveness of nursing directly affects the recovery effect and prognosis of patients. In recent years, nursing intervention based on time concept has begun to be popularized and applied in clinical practice. Time nursing measures combined with routine nursing are more conducive to improving patients nursing satisfaction, promoting the harmonious development of nurse-patient relationship, and improving patients psychological state and quality of life. Compared with routine nursing, it has more clinical advantages and has achieved ideal results. Based on this, this article will review the related research of time nursing on stroke patients from the aspects of overview and implementation strategies, and put forward suggestions and prospects for future research, in order to provide reference for time nursing-based intervention for stroke patients.

Evaluation of preoperative visceral fat area / psoas muscle area ratio and prognosis in patients with colorectal cancer

AbstractBackgroundRecent research has focused on the prognostic relevance of preoperative sarcopenia and sarcopenic obesity in various cancers. In this study we investigated the relationship between visceral fat area (VFA), psoas muscle area (PMA), and the prognosis of patients undergoing colorectal cancer surgery.MethodsPatients with stage III colorectal cancer who underwent surgery between July 2013 and April 2020 were included. The analysis was performed on 151 patients who met the criteria. The VFA and PMA were measured at the level of the third lumbar vertebra on computed tomography (CT) scans, and the ratio of VFA to PMA (V/P ratio) was determined.ResultsPatients with high V/P ratios were significantly older (p = 0.0213), had a higher body mass index (BMI) (p &lt; 0.0001), a higher percentage of sarcopenic obesity (p &lt; 0.0001), and more diabetes complications (p &lt; 0.0001). Prognostic analysis showed that the overall survival (OS) (p = 0.0154) and relapse‐free survival (RFS) (p = 0.0378) were significantly worse in patients with a high V/P ratio. Multivariate analysis revealed that a high V/P ratio was an independent poor prognostic factor for OS. Subgroup analysis was then performed in patients with BMI &lt; 25 kg/m2. OS (p = 0.0259) and RFS (p = 0.0275) were significantly worse in the high V/P ratio group. A high V/P ratio was an independent poor prognostic factor in the multivariate analysis.ConclusionIn colorectal cancer, the preoperative V/P ratio is an independent factor for poor prognosis. Preoperative evaluation of the V/P ratio may identify a wide range of high‐risk patients because it is an independent poor prognostic factor in patients without obesity.

Low Amplitude of Ocular Vestibular-Evoked Myogenic Potentials Can Denote Poor Prognosis in Patients with Idiopathic Sudden Sensorineural Hearing Loss

Low Amplitude of Ocular Vestibular-Evoked Myogenic Potentials Can Denote Poor Prognosis in Patients with Idiopathic Sudden Sensorineural Hearing Loss

18F-fluorodeoxyglucose positron emission tomography/computed tomography parameters are associated with histological outcomes in superficial esophageal squamous cell carcinoma

Endoscopic submucosal dissection is a standard treatment for early esophageal squamous cell carcinoma. However, submucosal or lymphovascular invasion increases the risk of lymph node metastasis. Although 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) parameters are associated with prognosis in patients with advanced esophageal squamous cell carcinoma, the utility of FDG PET/CT in diagnosing superficial esophageal carcinoma remains unclear. This study aimed to investigate the association between FDG PET/CT parameters and histopathological findings in superficial esophageal carcinoma. Fifty-three patients with superficial esophageal cancer who underwent FDG PET/CT scans before undergoing interventions were retrospectively analyzed. The maximal standardized uptake value (SUVmax), metabolic tumor volume, and total lesion glycolysis were significantly higher in the cases with submucosal invasion (T1b) compared with those confined to the muscularis mucosa (T1a). In contrast, classification of intrapapillary capillary loops patterns with magnifying endoscopy did not yield statistical differences between T1a and T1b. Multivariable analysis revealed that SUVmax was the only independent predictor of submucosal and lymphovascular invasion. This study demonstrated that SUVmax may be useful in predicting submucosal and lymphovascular invasion. Thus, the value of SUVmax may guide clinical decision-making in superficial esophageal squamous cell carcinoma.

Nanoparticles (NPs)-mediated lncMALAT1 silencing to reverse cisplatin resistance for effective hepatocellular carcinoma therapy

Platinum-based chemotherapy has been widely used for clinical cancer treatment, but drug resistance is the main barrier to induce the poor prognosis of cancer patients. Long non-coding RNAs (lncRNAs) have been recognized as a type of new cancer therapeutic targets due to their important role in regulating cancer progression such as drug resistance. However, it is still challenged to effectively intervene the expression of lncRNAs as they are usually located at various subcellular organelles (e.g., nucleus, mitochondrion, and endoplasmic reticulum). We herein developed an endosomal pH-responsive nanoparticle (NP) platform for small interfering RNA (siRNA) and cisplatin prodrug co-delivery and effective cisplatin-resistant hepatocellular carcinoma (HCC) therapy. This co-delivery nanoplatform is comprised of a hydrophilic polyethylene glycol (PEG) shell and a hydrophobic poly (2-(diisopropylamino)ethyl methacrylate) (PDPA) core, in which cisplatin prodrug and electrostatic complexes of nucleus-targeting amphiphilic peptide (NTPA) and siRNA are encapsulated. After intravenous injection and then uptake by tumor cells, the endosomal pH could trigger the dissociation of nanoplatform and enhance the endosomal escape of loaded cisplatin prodrug and NTPA/siRNA complexes via the “proton sponge” effect. Subsequently, the NTPA/siRNA complexes could specifically transport siRNA into the nucleus and efficiently reverse cisplatin resistance via silencing the expression of lncRNA metastasis-associated lung adenocarcinoma transcript 1 (lncMALAT1) mainly localized in the nucleus, ultimately inhibiting the growth of cisplatin-resistant HCC tumor.

Severe weight loss during PD-1 treatment is a risk sign of poor prognosis for advanced GC patients.

To verify whether severe weight loss is a reasonable risk sign for the effect of PD-1 treatment in advanced gastric cancer (GC) patients. 127 metastatic or recurrent GC patients treated with PD-1 inhibitors in Xuzhou Central Hospital were involved in this study. Two cohorts with different variables were built; one was used to reveal the relationship between body weight loss and overall survival (OS), and the other was used to find which body composition contributed to the weight loss. Variables were collected at PD-1 inhibitor initiation (baseline) and week 6 of treatment. Patients were followed up from the end of therapy to November 2022. Overall survival(OS) and disease-free survival (DFS) were recorded. 127 patients with metastatic/recurrent gastric cancer received PD-1 treatment, among whom 117 had complete weight data. After screening, data from 69 patients were used for body composition assessment. The study found that 33 patients who lost more than 2% of their body weight within six weeks had poorer OS and DFS, with medians of 9.5months and 6months, respectively. Cox regression analysis showed that weight loss of more than 2% and treatment methods was an independent risk for poor OS and DFS. Further analysis revealed that weight loss was mainly caused by a reduction in adipose tissue, rather than muscle mass. Severe weight loss is a potential monitor for the treatment effect of PD-1 inhibitor in advanced GC patients.

Early prediction of microvascular invasion (MVI) occurrence in hepatocellular carcinoma (HCC) by 18F-FDG PET/CT and laboratory data

BackgroundHepatocellular carcinoma (HCC) is one of the deadliest malignant tumors in China. Microvascular invasion (MVI) often indicates poor prognosis and metastasis in HCC patients. 18F-FDG PET–CT is a new imaging method commonly used to screen for tumor occurrence and evaluate tumor stage.PurposeThis study attempted to predict the occurrence of MVI in early-stage HCC through 18F-FDG positron emission tomography (PET)/computed tomography (CT) imaging findings and laboratory data.Patients and methodsA total of 113 patients who met the inclusion criteria were divided into two groups based on postoperative pathology: the MVI-positive group and MVI-negative group. We retrospectively analyzed the imaging findings and laboratory data of 113 patients. Imaging findings included tumor size, tumor maximum standard uptake value (SUVmaxT), and normal liver maximum standard uptake value (SUVmaxL). The ratios of SUVmaxT to SUVmaxL (SUVmaxT/L) and an SUVmaxT/L > 2 were defined as active tumor metabolism. The tumor size was indicated by the maximum diameter of the tumor, and a diameter greater than 5 cm was defined as a mass lesion. The laboratory data included the alpha-fetoprotein (AFP) level and the HBeAg level. An AFP concentration > 20 ng/mL was defined as a high AFP level. A HBeAg concentration > 0.03 NCU/mL was defined as HB-positive.ResultsThe SUVmaxT/L (p = 0.003), AFP level (p = 0.008) and tumor size (p = 0.015) were significantly different between the two groups. Patients with active tumor metabolism, mass lesions and high AFP levels tended to be MVI positive. Binary logistic regression analysis verified that active tumor metabolism (OR = 4.124, 95% CI, 1.566–10.861; p = 0.004) and high AFP levels (OR = 2.702, 95% CI, 1.214–6.021; p = 0.015) were independent risk factors for MVI. The sensitivity of the combination of these two independent risk factors predicting HCC with MVI was 56.9% (29/51), the specificity was 83.9% (52/62) and the accuracy was 71.7% (81/113).ConclusionActive tumor metabolism and high AFP levels can predict the occurrence of MVI in HCC patients.

Computer-aided prognosis of tuberculous meningitis combining imaging and non-imaging data

Tuberculous meningitis (TBM) is the most lethal form of tuberculosis. Clinical features, such as coma, can predict death, but they are insufficient for the accurate prognosis of other outcomes, especially when impacted by co-morbidities such as HIV infection. Brain magnetic resonance imaging (MRI) characterises the extent and severity of disease and may enable more accurate prediction of complications and poor outcomes. We analysed clinical and brain MRI data from a prospective longitudinal study of 216 adults with TBM; 73 (34%) were HIV-positive, a factor highly correlated with mortality. We implemented an end-to-end framework to model clinical and imaging features to predict disease progression. Our model used state-of-the-art machine learning models for automatic imaging feature encoding, and time-series models for forecasting, to predict TBM progression. The proposed approach is designed to be robust to missing data via a novel tailored model optimisation framework. Our model achieved a 60% balanced accuracy in predicting the prognosis of TBM patients over the six different classes. HIV status did not alter the performance of the models. Furthermore, our approach identified brain morphological lesions caused by TBM in both HIV and non-HIV-infected, associating lesions to the disease staging with an overall accuracy of 96%. These results suggest that the lesions caused by TBM are analogous in both populations, regardless of the severity of the disease. Lastly, our models correctly identified changes in disease symptomatology and severity in 80% of the cases. Our approach is the first attempt at predicting the prognosis of TBM by combining imaging and clinical data, via a machine learning model. The approach has the potential to accurately predict disease progression and enable timely clinical intervention.

A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning.

Endometrial cancer (EC) is a fatal gynecologic tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in EC. In this study, we explored the prognostic value of cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, and its correlation with immune infiltrates in EC. Transcriptome and somatic mutation profiles of EC were downloaded from TCGA database. Based on their stemness signature and DEGs, EC patients were divided into two subtypes via consensus clustering, and patients in Stemness Subtype I presented significantly better OS and DFS than Stemness Subtype II. Subtype I also displayed better clinicopathological features, and genomic variations demonstrated different somatic mutation from subtype II. Additionally, two stemness subtypes had distinct tumor immune microenvironment patterns. In the end, three machine learning algorithms were applied to construct a 7-gene stemness subtype risk model, which were further validated in an external independent EC cohort in our hospital. This novel stemness-based classification could provide a promising prognostic predictor for EC and may guide physicians in selecting potential responders for preferential use of immunotherapy. This novel stemness-dependent classification method has high value in predicting the prognosis, and also provides a reference for clinicians in selecting sensitive immunotherapy methods for EC patients.

MiR-93-5p inhibits ovarian cancer through SLC7A11-mediated-ferroptosis

AimOvarian cancer (OC) is the most lethal gynecological malignancy, which seriously affects the prognosis and life quality of female patients. Therefore, new therapeutic targets and treatments are urgently needed. MethodsExpression levels of miR-93-5p and SLC7A11 and ferroptosis status in paracancerous and tumor tissues were examined and compared. The effect of the miR-93-5p-SLC7A11 regulatory loop on the malignant phenotype as well as the ferroptosis phenotype of SKOV3 cells was assessed. Furthermore, the interaction between miR-93-5p and SLC7A11 was confirmed via rescue experiment. ResultsIn this study, we found that miR-93-5p was lowly expressed in cancer tissues, and suggested that overexpression of miR-93-5p could target SLC7A11 to reduce its expression and promote ferroptosis, thereby inhibiting the malignant biological behaviors such as proliferation, invasion and migration, while knockdown of miR-93-5p restrained ferroptosis and promoting tumor growth. Besides, erastin, as a specific inhibitor of SLC7A11, could target down the expression of SLC7A11, induce the occurrence of ferroptosis, and reverse the effect of knockdown of miR-93-5p. ConclusionsTaken together, our findings disclosed that miR-93-5p increased the level of ferroptosis and inhibited the progression of OC by targeting and inhibiting the expression level of SLC7A11, which was a potential treatment in OC.

HOXC11-mediated regulation of mitochondrial function modulates chemoresistance in colorectal cancer

BackgroundChemoresistance remains a significant challenge in colorectal cancer (CRC) treatment, necessitating a deeper understanding of its underlying mechanisms. HOXC11 has emerged as a potential regulator in various cancers, but its role in CRC chemoresistance remains unclear.MethodsSulforhodamine B assay was employed to assess the cell viability of CRC cells following treatment with chemotherapeutic drugs. Immunofluorescence staining was performed to examine the subcellular localization of HOXC11 in normal and chemoresistant CRC cells. The Seahorse mito stress test was conducted to evaluate the mitochondrial respiratory function of CRC cells. Real-time PCR was utilized to measure the expression level and copy number of mitochondrial DNA (mtDNA).ResultsOur findings revealed that HOXC11 was overexpressed in CRC cells compared to normal colorectal cells and correlated with poorer prognosis in CRC patients. Knockout of HOXC11 reversed acquired chemoresistance in CRC cells. Furthermore, we observed a functional subset of HOXC11 localized to the mitochondria in chemoresistant CRC cells, which regulated mitochondrial function by modulating mtDNA transcription, thereby affecting chemoresistance.ConclusionsIn summary, our study reveals that HOXC11 regulates mitochondrial function through the modulation of mtDNA transcription, impacting chemoresistance in colorectal cancer cells. These findings underscore the significance of understanding the molecular mechanisms underlying chemoresistance and highlight the potential therapeutic implications of targeting mitochondrial function in CRC treatment.

Homologous recombination deficiency status predicts response to immunotherapy-based treatment in non-small cell lung cancer patients.

Homologous recombination deficiency (HRD) is a biomarker that predicts response to ovarian cancer treatment with poly (ADP-ribose) polymerase (PARP) inhibitors or breast cancer treatment with first-line platinum-based chemotherapy. However, there are few studies on the prognosis of lung cancer patients treated with immune checkpoint inhibitor (ICI) therapy using HRD as a biomarker. We studied the relationship between HRD status and the effectiveness of first-line ICI-based therapy in EGFR/ALK wild-type metastatic non-small cell lung cancer patients (NSCLC) patients. This study included 22 treatment naïve NSCLC patients. The HRD score ranged from -26.37 to 92.34, with an average of 24.57. Based on analysis of the progression-free survival (PFS) data from the included NSCLC patients, threshold traversal was carried out. HRD (+) was defined as an HRD score of 31 or higher. Kaplan-Meier PFS survival analysis showed prolonged median PFS (mPFS) in NSCLC patients with HRD (+) versus HRD (-) (N/A vs. 7.0 ms, log-rank p = 0.029; HR 0.20, 95% CI: 0.04-0.96, likelihood-ratio p = 0.03). In patients with PD-L1 TPS ≥50% and HRD score ≥31 (co-status high), the mPFS was temporarily not reached during the follow-up period. In patients with PD-L1 TPS <1% and HRD score <31, the mPFS was 3 ms. Cox regression analysis showed that the hazard ratio of the co-status was 0.14 (95% CI: 0.04-0.54), which was a good prognostic factor, and the prognostic effect of co-status was better than that of HRD score alone. The HRD status can be identified as an independent significance in NSCLC patients treated with first-line ICI-based therapy.

A preoperative radiogenomic model based on quantitative heterogeneity for predicting outcomes in triple-negative breast cancer patients who underwent neoadjuvant chemotherapy

BackgroundTriple-negative breast cancer (TNBC) is highly heterogeneous, resulting in different responses to neoadjuvant chemotherapy (NAC) and prognoses among patients. This study sought to characterize the heterogeneity of TNBC on MRI and develop a radiogenomic model for predicting both pathological complete response (pCR) and prognosis.Materials and methodsIn this retrospective study, TNBC patients who underwent neoadjuvant chemotherapy at Fudan University Shanghai Cancer Center were enrolled as the radiomic development cohort (n = 315); among these patients, those whose genetic data were available were enrolled as the radiogenomic development cohort (n = 98). The study population of the two cohorts was randomly divided into a training set and a validation set at a ratio of 7:3. The external validation cohort (n = 77) included patients from the DUKE and I-SPY 1 databases. Spatial heterogeneity was characterized using features from the intratumoral subregions and peritumoral region. Hemodynamic heterogeneity was characterized by kinetic features from the tumor body. Three radiomics models were developed by logistic regression after selecting features. Model 1 included subregional and peritumoral features, Model 2 included kinetic features, and Model 3 integrated the features of Model 1 and Model 2. Two fusion models were developed by further integrating pathological and genomic features (PRM: pathology-radiomics model; GPRM: genomics-pathology-radiomics model). Model performance was assessed with the AUC and decision curve analysis. Prognostic implications were assessed with Kaplan‒Meier curves and multivariate Cox regression.ResultsAmong the radiomic models, the multiregional model representing multiscale heterogeneity (Model 3) exhibited better pCR prediction, with AUCs of 0.87, 0.79, and 0.78 in the training, internal validation, and external validation sets, respectively. The GPRM showed the best performance for predicting pCR in the training (AUC = 0.97, P = 0.015) and validation sets (AUC = 0.93, P = 0.019). Model 3, PRM and GPRM could stratify patients by disease-free survival, and a predicted nonpCR was associated with poor prognosis (P = 0.034, 0.001 and 0.019, respectively).ConclusionMultiscale heterogeneity characterized by DCE-MRI could effectively predict the pCR and prognosis of TNBC patients. The radiogenomic model could serve as a valuable biomarker to improve the prediction performance.

Machine learning-based screening and validation of liver metastasis-specific genes in colorectal cancer

Colorectal liver metastasis (CRLM) is challenging in the clinical treatment of colorectal cancer. Limited research has been conducted on how CRLM develops. RNA sequencing data were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Four machine learning algorithms were used to screen the hub CRLM-specific genes, including Least Absolute Shrinkage and Selection Operator (Lasso), Random forest, SVM-RFE, and XGboost. The model for identifying CRLM was developed using stepwise logistic regression and was validated using internal and independent datasets. The prognostic value of hub CRLM-specific genes was assessed using the Lasso-Cox method. The in vitro experiments were performed using SW620 cells. The CRLM identification model was developed based on four CRLM-specific genes (SPP1, ZG16, P2RY14, and PRKAR2B), and the model efficacy was validated using GSE41258 and three external cohorts. Five CRLM-specific prognostic hub genes, SPP1, ZG16, P2RY14, CYP2E1, and C5, were identified using the Lasso-Cox algorithm, and a risk score was constructed. The risk score was validated using the GSE39582 cohort. Three genes have both efficacy in identifying CRLM and prognostic value: ZG16, P2RY14, and SPP1. Immune infiltration and enrichment analyses demonstrated that SPP1 was associated with M2 macrophage polarization and extracellular matrix remodeling. In vitro experiments indicated that SPP1 may act as a cancer-promoting factor. The hub CRLM-specific gene SPP1 can help determine the diagnosis, prognosis, and immune infiltration of patients with CRLM.

Trim21-mediated CCT2 ubiquitination suppresses malignant progression and promotes CD4+T cell activation in breast cancer

Breast cancer remains a significant global health challenge, and its mechanisms of progression and metastasis are still not fully understood. In this study, analysis of TCGA and GEO datasets revealed a significant increase in CCT2 expression in breast cancer tissues, which was associated with poor prognosis in breast cancer patients. Functional analysis revealed that CCT2 promoted breast cancer growth and metastasis through activation of the JAK2/STAT3 signaling pathway. Additionally, the E3 ubiquitin ligase Trim21 facilitated CCT2 ubiquitination and degradation, significantly reversing the protumor effects of CCT2. Most interestingly, we discovered that exosomal CCT2 derived from breast cancer cells suppressed the activation and proinflammatory cytokine secretion of CD4+ T cell. Mechanistically, exosomal CCT2 constrained Ca2+-NFAT1 signaling, thereby reducing CD40L expression on CD4+ T cell. These findings highlight CCT2 upregulation as a potential driver of breast cancer progression and immune evasion. Our study provides new insights into the molecular mechanisms underlying breast cancer progression, suggesting that CCT2 is a promising therapeutic target and prognostic predictor for breast cancer.

Derived Neutrophils to Lymphocyte Ratio Predicts Survival Benefit from TPF Induction Chemotherapy in Local Advanced Oral Squamous Cellular Carcinoma

Background: This study aimed to evaluate the derived neutrophil to lymphocyte ratio (dNLR) in predicting the prognosis of patients with locally advanced oral squamous cell carcinoma (LAOSCC) and to assess the survival benefits from docetaxel, cisplatin, and 5-fluorouracil (5-FU) (TPF) induction chemotherapy (IC). Methods: Patients from a phase III trial involving TPF IC in stage III/IVA OSCC patients (NCT01542931) were enrolled. Receiver operating characteristic curves were constructed, and the area under the curve was computed to determine dNLR cutoff points. Kaplan–Meier survival estimates and Cox proportional hazards models were used for longitudinal analysis. Results: A total of 224 patients were identified (median age: 55.4 years; range: 26 to 75 years; median follow-up: 90 months; range: 3.2 to 93 months). The cutoff point for the dNLR was 1.555. Multivariate analysis showed that the dNLR was an independent negative predictive factor for survival (overall survival (OS): hazard ratio (HR) = 1.154, 95% confidence interval (CI): 1.018–1.309, p = 0.025; disease-free survival (DFS): HR = 1.123, 95% CI: 1.000–1.260, p = 0.050; local recurrence-free survival (LRFS): HR = 1.134, 95% CI: 1.002–1.283, p = 0.047; distant metastasis-free survival (DMFS): HR = 1.146, 95% CI: 1.010–1.300, p = 0.035). A low dNLR combined with cTNM stage III disease predicted benefit from TPF IC for the patients [OS (χ2 = 4.674, p = 0.031), DFS (χ2 = 7.134, p = 0.008), LRFS (χ2 = 5.937, p = 0.015), and DMFS (χ2 = 4.832, p = 0.028)]. Conclusions: The dNLR is an independent negative predictive factor in LAOSCC patients. Patients with cTNM stage III disease and a low dNLR can benefit from TPF IC.

In Vitro and In Vivo Effects of Melatonin-Containing Combinations in Human Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) has poor prognosis and high mortality rates. Therefore, it is necessary to identify new targets and therapeutic strategies to improve the prognosis of patients with PDAC. Integrative therapies are increasingly being used to boost the efficacy of the known anticancer therapeutic approaches. Hence, this study aimed to evaluate the effects of a novel combination of different potential anticancer molecules, melatonin (MLT), cannabidiol (CBD), and oxygen-ozone (O2/O3) to treat PDAC using in vitro and in vivo models of human PDAC. The effect of this combination was investigated in combination with gemcitabine (GEM), the most common chemotherapeutic drug used for PDAC treatment. The combination of MLT + CBD + O2/O3 was more effective than the individual treatments in inhibiting PDAC cell viability and proliferation, inducing cell death, and modulating the RAS pathway protein levels. Moreover, different combinations of treatments reduced tumor mass in the PDAC mouse model, thus promoting the effect of GEM. In conclusion, a mixture of MLT + CBD + O2/O3 couldserve as a potential adjuvant therapeutic strategy for PDAC.