Since over one-third of DLBCL patients experience relapse or refractory after standard therapy, high-risk patients must be predicted. We developed a prognostic immune-related gene pairs (IRGPs) signature for DLBCL patients using bioinformatics analyses. This signature can predict the prognosis of these patients adequately, either alone or in combination with other clinical parameters. It hopes to improve the stratification and management of these patients for broad clinical applications.

Head and neck squamous cell carcinoma ranks seventh globally in malignancy prevalence, with persistent high mortality rates despite treatment advancements. Glucose, pivotal in cancer metabolism via the Warburg effect, enters cells via glucose transporters, notably GLUT proteins. Glycolysis, aerobic oxidation, and the pentose phosphate pathway in glucose metabolism significantly impact HNSCC progression. HNSCC exhibits elevated expression of glucose metabolism enzymes and GLUT proteins, correlating with prognosis. Heterogeneity in HNSCC yields varied metabolic profiles, influenced by factors like HPV status and disease stage. This review highlights glucose metabolism's role and potential as therapeutic targets and cancer imaging tracers in HNSCC.

To investigate the effects of LDHB on lactylation of programmed cell death 1 ligand (PD-L1) and immune evasion of ovarian cancer.

The aim of this work was to explore the use of an original once-weekly radiotherapy fractionation in elderly or frail patients with recurrence or metastasis from different solid malignancies.

Recent advancements in analytical techniques have highlighted the potential of Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy as a quick, cost-effective, non-invasive, and efficient tool for cancer diagnosis. This study aims to evaluate the effectiveness of ATR-FTIR spectroscopy in combination with supervised machine learning classification models for diagnosing OSCC using saliva samples.

Evidence with regards to the distinction between primary and metastatic tumors in pancreatic cancer and driving factors for metastases remains limited.

Skin cancer (SC) is one of the three most common cancers worldwide. Melanoma has the deadliest potential to spread to other parts of the body among all SCs. For SC treatments to be effective, early detection is essential. The high degree of similarity between tumor and non-tumors makes SC diagnosis difficult even for experienced doctors. To address this issue, authors have developed a novel Deep Learning (DL) system capable of automatically classifying skin lesions into seven groups: actinic keratosis (AKIEC), melanoma (MEL), benign keratosis (BKL), melanocytic Nevi (NV), basal cell carcinoma (BCC), dermatofibroma (DF), and vascular (VASC) skin lesions. Authors introduced the Multi-Grained Enhanced Deep Cascaded Forest (Mg-EDCF) as a novel DL model. In this model, first, researchers utilized subsampled multigrained scanning (Mg-sc) to acquire micro features. Second, authors employed two types of Random Forest (RF) to create input features. Finally, the Enhanced Deep Cascaded Forest (EDCF) was utilized for classification. The HAM10000 dataset was used for implementing, training, and evaluating the proposed and Transfer Learning (TL) models such as ResNet, AlexNet, and VGG16. During the validation and training stages, the performance of the four networks was evaluated by comparing their accuracy and loss. The proposed method outperformed the competing models with an average accuracy score of 98.19%. Our proposed methodology was validated against existing state-of-the-art algorithms from recent publications, resulting in consistently greater accuracies than those of the classifiers.

Endometrial cancer (EC) is a common gynecological malignancy and its mortality has been increasing in the last twenty years. A growing body of evidence suggests that circulating tumor cells (CTCs) may provide a more complete tumor profile, facilitate the understanding of the molecular mechanism and individual management of EC patients. In this review, we presented the presence and clinical applications of CTCs and disseminated tumor cells (DTCs) in EC, particularly for EC prognosis and management, also highlighted the diagnostic value of tumor cells in urine of EC patients, aim to help researchers better focus on their study in this field.

Despite a biologically established causative role of viral hepatitis (VH), i.e. HBV and HCV infections, on intrahepatic cholangiocarcinoma (ICC), only few large Western cohorts exploring the association between VH and ICC development are available. The prognostic significance of VH in ICC is debated, and no data are available regarding a predictive role for standard first-line CT (CT1), consisting of gemcitabine +/- platinoids. VH-positivity definition is often clinically incomplete and inconsistent among studies. Five different VH conditions, based on laboratory and anamnestic data, were investigated in a multicentric retrospective cohort of advanced ICC cases. Depending on the specific VH condition considered, 139-194 of 472 ICC cases could be categorized according to the presence of the mentioned VH conditions. VH prevalence ranged from 9.3 to 25.3%. No VH condition showed an impact on survival, although a non-significant worse outcome was observed for some HBV-related conditions. HCV-related conditions were associated to lower pre-CT1 biomarkers of inflammation, markedly higher disease control, and numerically longer time-to-progression with CT1. No benefit on time-to-progression was demonstrated for the addition of platinoids to gemcitabine in VH-positive patients (HR 0.77, CI 0.41-1.45), at least in HBV-related cases. These findings are clinically relevant and deserve further investigation.

Breast cancer with increased risk in women is identified with Breast Magnetic Resonance Imaging (Breast MRI) and this helps in evaluating treatment therapies. Breast MRI is time time-consuming process that involves the assessment of current imaging. This research work depends on the detection of breast cancer at the earlier stages. Among various cancers, breast cancer in women occurs in larger accounts for almost 30% of estimated cancer cases. In this research, many steps are followed for breast cancer detection like pre-processing, segmentation, augmentation, extraction of features, and cancer detection. Here, the median filter is utilized for pre-processing, as well as segmentation is followed after pre-processing, which is done by Psi-Net. Moreover, the process of augmentation like shearing, translation, and cropping are followed after segmentation. Also, the segmented image tends to process feature extraction, where features like shape features, Completed Local Binary Pattern (CLBP), Pyramid Histogram of Oriented Gradients (PHOG), and statistical features are extracted. Finally, breast cancer is detected using the DL model, SqueezeNet. Here, the newly devised Flamingo Search SailFish Optimizer (FSSFO) is used in training Psi-Net as well as SqueezeNet. Furthermore, FSSFO is the combination of both the Flamingo Search Algorithm (FSA) and SailFish Optimizer (SFO).

Triple-negative breast cancer (TNBC) is known to have the worst outcome compared to the other forms of breast cancer. Moreover, molecular markers identified basal-like breast cancer (BLBC) phenotypes to be also related to a worse prognosis. In this study, we evaluated by immunohistochemistry (IHC) the prognostic significance of combining Cytokeratin-19 (CK19), E-cadherin, and Ki-67 tissue expression in triple-negative breast cancer (TNBC) cases presenting a basal-like (BLBC) or a non-basal-like (n-BLBC) phenotype to improve the selection and the monitoring of BC patients with a more aggressive outcome. Herein, when compared to n-BLBC, patients with BLBC showed a positive correlation with lymph node metastasis occurrence and lower survival rates. Immunohistochemistry analysis revealed significantly lower E-cadherin prevalence and higher prevalence of both CK19 and Ki-67 in BLBC when compared to n-BLBC. Spearman correlation showed that E-cadherin is negatively and significantly correlated to CK19 and Ki-67 expressions. Moreover, in BLBC, expressing both CK19 and Ki-67 combined with E-cadherin loss was associated with the worst relapse-free and overall survival. In conclusion, TNBC/BLBC phenotypes simultaneously losing E-cadherin and overexpressing CK19 and Ki-67 markers are the most aggressive forms. This combined analysis could be a predictive marker of poor prognosis.

Primary pulmonary salivary gland tumors (PSGT) constitute a rare subtype of non-small cell lung cancer (NSCLC). Currently, no established treatment guidelines exist for advanced PSGT. The efficacy of platinum-based chemotherapy for PSGT within the context of NSCLC remains uncertain. Therefore, we retrospectively collected 37 PSGT patients who underwent first-line platinum-based chemotherapy from 2010 to 2023. Survival analysis, employing the Kaplan-Meier method, and group comparisons via the log rank test were conducted. Our results show that first-line platinum-based chemotherapy demonstrates favorable efficacy and manageable safety in advanced PSGT, with the combination of Paclitaxel + Platinum emerging as a preferred option.

Although several observational studies have reported a link between the use of underarm cosmetic products and the risk of breast cancer, the findings remain inconsistent. This study aimed to investigate these associations using a meta-analysis of observational studies. In the meta-analysis of seven case-control studies, we found no association between the use of underarm antiperspirants or deodorants and the risk of breast cancer (OR = 0.96, 95%CI 0.78-1.17;  = 60.0%). Further prospective cohort studies that provide a higher level of evidence are warranted to confirm our findings.

Invasive cribriform carcinoma (ICC) is a type of malignant tumor with slow growth and good prognosis. The study was a single center retrospective study. The percentage of ICC among patients diagnosed with breast cancer was 0.3% (8/2454 patients). All patients tested positive for estrogen or progesterone receptors and 12.5% (1/8) patients tested positive for human epidermal growth factor receptor type2 (HER2). The present study suggests that the clinicopathological features of ICC are low-grade hormone receptor-positive luminal type with a good prognosis. However, some patients were HER2-positive and require careful follow-up.

Limited research has compared cognition of people with non-central nervous system metastatic cancer (NCM) metastatic brain cancer (BM). This prospective cross-sectional study was comprised 37 healthy controls (HC), 40 NCM, and 61 BM completing 10 neuropsychological tests. The NCM performed below HCs on processing speed and executive functioning tasks, while the BM group demonstrated lower performance across tests. Tasks of processing speed, verbal fluency, and verbal memory differentiated the clinical groups (BM < NCM). Nearly 20% of the NCM group was impaired on three neuropsychological tests whereas approximately 40% of the BM group demonstrated the same level of impairment.

We aimed to examine the relationship between body image and the meaning of life among women with breast cancer. The analytic sample included 142 women with breast cancer, and data were collected using a standardized questionnaire through face-to-face interviews. We used Kolmogorov-Smirnov test, Pearson test, Spearman and Mann-Whitney U test to determine the relationship between the research variables. We found an association between the mean score of body image and the mean score of the meaning of life. As the average score of body image increases, the score of the meaning of life increases ( < 0.05). Findings indicated that the body image score increases by increasing the score of the meaning of life and its dimensions, especially existential vacuum and acceptance of death. Future research and targeted treatments should consider the role of body image in shaping the meaning of life among women with breast cancer.

A minority of patients with MSS tumors present a high tumor mutation burden (TMB) without underlying MMR defects.

This work proposed a liver cancer classification scheme that includes Preprocessing, Feature extraction, and classification stages. The source images are pre-processed using Gaussian filtering. For segmentation, this work proposes a LUV transformation-based adaptive thresholding-based segmentation process. After the segmentation, certain features are extracted that include multi-texon based features, Improved Local Ternary Pattern (LTP-based features), and GLCM features during this phase. In the Classification phase, an improved Deep Maxout model is proposed for liver cancer detection. The adopted scheme is evaluated over other schemes based on various metrics. While the learning rate is 60%, an improved deep maxout model achieved a higher -measure value (0.94) for classifying liver cancer; however, the previous method like Support Vector Machine (SVM), Random Forest (RF), Recurrent Neural Network (RNN), Long Short Term Memory (LSTM), K-Nearest Neighbor (KNN), Deep maxout, Convolutional Neural Network (CNN), and DL model holds less -measure value. An improved deep maxout model achieved minimal False Positive Rate (FPR), and False Negative Rate (FNR) values with the best outcomes compared to other existing models for liver cancer classification.

The role of tweety homolog 3 (TTYH3) has been studied in several cancers, including hepatocellular carcinoma, cholangiocarcinoma, and gastric cancer. The results showed that TTYH3 is highly expression in cervical cancer tissues and cells and high TTYH3 expression correlates with poor prognosis in patients with cervical cancer. TTYH3 markedly reduced the apoptosis rate and promoted proliferation, migration, and invasion. Silencing of TTYH3 has been shown to have an inhibitory effect on cervical cancer progression. Moreover, TTYH3 enhanced EMT and activated Wnt/β-catenin signaling. Furthermore, TTYH3 knockdown inhibited the tumor growth in vivo. In conclusion, TTYH3 promoted cervical cancer progression by activating the Wnt/β-catenin signaling.

In this study, we retrospectively analysed the efficacy and safety of three treatment models, namely, short-course radiotherapy sequential XELOX chemotherapy, neoadjuvant mFOLFOX6 concurrent radiotherapy and long-course concurrent radiotherapy with total mesorectal excision (TME) after treatment of locally advanced rectal cancer with high-risk factors.