Hematological and Serum Biochemical Changes and Their Prognostic Value in Horses Spontaneously Poisoned by Crotalaria spectabilis

Determining the prognosis of poisoning by plants containing pyrrolizidine alkaloids is usually challenging. This study aimed to identify important prognostic parameters that can determine the severity of spontaneous poisoning by Crotalaria spectabilis in horses. Blood samples from 42 horses spontaneously poisoned by oats contaminated with C. spectabilis seeds were evaluated. Complete blood counts (CBC) and serum biochemical tests [urea, creatinine, total protein, albumin, total and direct bilirubin concentrations, aspartate aminotransferase (AST), γ-glutamyl transferase (GGT), and creatine kinase (CK) activities] were performed. Horses were followed up for 12 months to determine the long-term survival rate; after 12 months, they were divided into two groups: survivors (n = 30) and non-survivors (n = 12). Horses spontaneously poisoned with C. spectabilis had higher levels of urea, globulin, bilirubin (total, direct, and indirect), AST, GGT, and CK than the reference values. Non-survivor horses showed significantly higher (p < 0.05) values of hemoglobin, GGT, and direct bilirubin than the survivor horses. Horses with serum GGT activity higher than 95 U/l had 14.0 times the risk of death compared to animals showing activities equal to or lower than this value, whereas horses with serum direct bilirubin concentration higher than 0.6 mg/dl (10.26 μmol/L) had 5.78 times the risk of death compared to the others. In summary, serum GGT activity and direct bilirubin concentration may be useful prognostic indicators for assessing the severity of C. spectabilis-poisoned horses.

Machine Learning Algorithms as a Computer-Assisted Decision Tool for Oral Cancer Prognosis and Management Decisions: A Systematic Review

<b><i>Introduction:</i></b> Despite multiple prognostic indicators described for oral cavity squamous cell carcinoma (OCSCC), its management still continues to be a matter of debate. Machine learning is a subset of artificial intelligence that enables computers to learn from historical data, gather insights, and make predictions about new data using the model learned. Therefore, it can be a potential tool in the field of head and neck cancer. <b><i>Methods:</i></b> We conducted a systematic review. <b><i>Results:</i></b> A total of 81 manuscripts were revised, and 46 studies met the inclusion criteria. Of these, 38 were excluded for the following reasons: use of a classical statistical method (<i>N</i> = 16), nonspecific for OCSCC (<i>N</i> = 15), and not being related to OCSCC survival (<i>N</i> = 7). In total, 8 studies were included in the final analysis. <b><i>Conclusions:</i></b> ML has the potential to significantly advance research in the field of OCSCC. Advantages are related to the use and training of ML models because of their capability to continue training continuously when more data become available. Future ML research will allow us to improve and democratize the application of algorithms to improve the prediction of cancer prognosis and its management worldwide.

Pancreatic ductal adenocarcinoma: Prognostic indicators of advanced disease

Background/Objectives Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy associated with high metastatic risk. Prognosis remains poor even after resection. Previously our group identified biomarkers that improved diagnostic accuracy in PDAC beyond the established diagnostic tumour marker, CA19-9. Risk factors, symptoms and circulating biomarkers associated with a PDAC diagnosis may differ from those that alter disease progression and metastasis. This study aimed at assessing the risk factors, presenting symptoms and potential prognostic biomarkers in PDAC and determine their relationship with PDAC stage and/or metastatic status. Methods Seventy-two PDAC patients with imaging available for TNM staging at presentation were enrolled following informed consent. Demographic and clinical data were captured. Blood was collected and 38 cytokines/angiogenic factors measured. Nonparametric association tests, univariate and multivariate logistic regression were performed using STATA version 14.2. A p-value≤0.05 was considered significant and odds ratios reported for effect size. Results Most risk factors and symptoms did not differ across the stages of cancer. Although male gender and smoking are risk factors for PDAC, the majority of study patients with metastatic PDAC were non-smoking females. In addition to CA19-9, the platelet count (p<0.01), IL-15 (p = 0.02) and GM-CSF (p<0.01) were significant, independent negative predictors of metastatic PDAC. Moreover, using specific cut-off values in a combined panel, the odds in a patient with all three biomarker levels below the cut-offs is 21 times more likely to have metastatic PDAC (p<0.0001). Conclusions Platelet count, IL-15 and GM-CSF are potential prognostic indicators of metastatic disease in PDAC patients from our local South African population.

Efficacy and Safety of the Combination of Nano-Liposomal Irinotecan and 5-Fluorouracil/L-Leucovorin in Unresectable Advanced Pancreatic Cancer: A Real-World Study

Aim: This retrospective study investigated the efficacy and safety of nano-liposomal irinotecan (nal-IRI) plus 5-fluorouracil/l-leucovorin (5-FU/l-LV) treatment in the second-line or later setting for advanced pancreatic cancer under real-world conditions.Methods: Between June 2020 and September 2021, a total of 44 patients with unresectable advanced pancreatic cancer treated with nal-IRI + 5-FU/l-LV in our affiliated hospitals were included. The prognosis, predictive factors (including systemic inflammation-based prognostic indicators), and adverse events were investigated.Results: The median age was 68 (interquartile range [IQR] 62-73) years old, and 22 patients (50.0%) were male. Concerning tumor factors, 9 patients (20.5%) had local advanced disease, and 35 patients (79.5%) had metastases. Twenty-five of the 44 patients were receiving second-line treatment, and 19 were receiving third-line or later treatment. The median overall survival (OS) and progression free survival (PFS) were 9.0 (range, 0.7-15.4) months and 4.4 (range, 0.6-15.4) months, respectively. The overall response rate (ORR) was 5.3%. The disease control rate (DCR) was 44.7%. Patients with a neutrophil-to-lymphocyte ratio (NLR) of >2.7 had a significant risk of a poor OS (HR=0.275, P=0.017). Adverse events were manageable, although gastrointestinal symptoms and neutropenia were observed. The most common grade ≥3 adverse event was neutropenia, which was reported in 20% of patients.Conclusions: Nal-IRI + 5-FU/l-LV therapy was considered to be a useful regimen as second-line or later treatment for unresectable advanced pancreatic cancer, even in clinical practice.

Establishment and Validation of Prognostic Nomograms for Patients With Parotid Gland Adenocarcinoma Not Otherwise Specified: A SEER Analysis From 2004 to 2016

Background: Parotid gland adenocarcinoma not otherwise specified (PANOS) is a rare malignant tumor with limited data on its characteristics and prognosis. This research is aimed at characterizing PANOS and developing prognostic prediction models for patients with PANOS.Methods: Cases from 2004–2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program database. Univariate and multivariate Cox regression were applied to ascertain the factors associated with survival. Competing risk analysis and Gray's tests were employed to analyze cancer-specific death. Propensity score matching (1:1) was conducted to reduce the influence of confounding variables.Results: A total of 446 patients with a median age of 66 years were selected, of which 307 were diagnosed with stage III/IV PANOS. The 5-year overall survival (OS) rate of all patients was 51.8%, and the median survival time was 66 months. Surgical treatment clearly improved survival time (p &lt; 0.001). In the subgroup analysis, radiotherapy showed survival benefits in patients with stage III/IV disease (p &lt; 0.001). Multivariate Cox regression analyses showed that age, T classification, N classification, M classification and surgery were independent prognostic indicators for OS; T classification, N classification, M classification and surgery were independent risk factors for cancer-specific survival (CSS). In addition, age was independently associated with other cause-specific death. Based on the results of multivariate analysis, two nomograms were developed and verified by the concordance index (C-index) (0.747 and 0.780 for OS and CSS) and the area under the time-dependent receiver operating characteristic (ROC) curve (0.756, 0.764, and 0.819 regarding for nomograms predicting 3-, 5-, and 10- year OS, respectively and 0.794, 0.789, and 0.806 for CSS, respectively).Conclusions: Our study clearly presents the clinicopathological features and survival analysis of patients with PANOS. In addition, our constructed nomogram prediction models may assist physicians in evaluating the individualized prognosis and deciding on treatment for patients.

Prognostic Biomarkers and Therapeutic Targets Identification Among CXC Chemokines in the Colon Adenocarcinoma Microenvironment

Background: COAD is among the most prevalent malignancy, with a very high incidence rate. Crosstalk between cancer and interstitial cells significantly affects cancer development, modulated partly by chemokines production. When present in the tumor microenvironment, CXC chemokines have been shown to regulate tumor cell activity and influence immune cell transport, resulting in anti-tumor immune mechanisms and influencing the outcomes of the patient; nonetheless, the CXC chemokines expression levels in COAD, as well as their prognostic significance, have not yet been established.Methods: This study used UALCAN, GeneMANIA, STRING, TRRUST, cBioPortal, TIMER, and GEPIA,Results: The expression of CXC1/2/3/5/6/11/12/13/14/16/17 in COAD patients was shown to be significantly correlated with the pathological stage. A considerably improved prognosis was observed in patients with low transcriptional levels of CXCL9/10/11. Differentially expressed CXC chemokines exert roles that are predominantly correlated with the chemokine signaling pathway and interactions of cytokine–cytokine receptors. Our findings indicated that the transcriptional factors, including SP1, RELA, and NFKB1 are essential for the production of CXC chemokines. Furthermore, we discovered a substantial association between the CXC chemokines production and infiltration of 6 kinds of immune cells (CD8+ T cells, dendritic cells, B cells, CD4+ T cells, neutrophils, and macrophages,). Conclusions: These findings might be useful in identifying prognostic indicators and immunotherapeutic targets for colon cancer.

Identification of Novel Prognostic Risk Signature of Breast Cancer Based on Ferroptosis-Related Genes

Ferroptosis is a non-small molecule-induced form of tumor cell apoptosis, which has been shown to regulate the biological behavior of tumors. Therefore, genes controlling ferroptosis may be promising candidate biomarkers for tumor therapy. In this study, we investigate the function of genes associated with ferroptosis in breast cancer (BC) and systematically evaluate the relationship between ferroptosis-related gene expression profiles and prognosis in BC patients based on the Cancer Genome Atlas RNA-sequencing dataset (TCGA). By using the non-negative matrix factorization clustering method, 1,203 breast cancer samples were clustered into two clearly divided subgroups based on the expression of 237 ferroptosis-related genes. The least absolute shrinkage and selection operator (LASSO) was used to develop risk profiles for five genes, and then these five genes were verified by the polymerase chain reaction (PCR). The relationship between genetic risk characteristics and clinical characteristics of BC is described. The results show that the genetic risk signature associated with clinical characteristics can be used as independent prognostic indicators for BC patients.

Identification of Multi-omics Biomarkers and Construction of the Novel Prognostic Model for Hepatocellular Carcinoma

Genome changes play a crucial role in carcinogenesis, and many biomarkers can be used as effective prognostic indicators in various tumours. Although previous studies have constructed many predictive models for hepatocellular carcinoma (HCC) based on molecular signatures, the performance is unsatisfactory. To fill this shortcoming, we hope to build a more accurate predictive model to guide prognostic assessments of HCC. We use the TCGA to identify crucial biomarkers and construct single-omic prognostic models through difference analysis, univariate Cox, and LASSO/stepwise Cox analysis. The performances of single-omic models were evaluated and validated through survival analysis, Harrell’s concordance index (C-index), and receiver operating characteristic (ROC) curve. A multi-omics model was built and evaluated by decision curve analysis (DCA), C-index, and ROC analysis. Multiple mRNAs, lncRNAs, miRNAs, CNV genes, and SNPs were significantly associated with the prognosis of HCC. Five single-omic models were constructed, and the mRNA and lncRNA models showed good performance with c-indexes over 0.70. The multi-omics model presented a quite predictive solid ability with a c-index over 0.80. In this study, we identified many biomarkers that may help study underlying carcinogenesis mechanisms in HCC. In addition, we constructed multiple single-omic models and an integrated multi-omics model that may provide practical and reliable guides for prognosis assessment and treatment decision-making.

Telomere and Telomerase-Associated Proteins in Endometrial Carcinogenesis and Cancer-Associated Survival

Risk of relapse of endometrial cancer (EC) after surgical treatment is 13% and recurrent disease carries a poor prognosis. Research into prognostic indicators is essential to improve EC management and outcome. “Immortality” of most cancer cells is dependent on telomerase, but the role of associated proteins in the endometrium is poorly understood. The Cancer Genome Atlas data highlighted telomere/telomerase associated genes (TTAGs) with prognostic relevance in the endometrium, and a recent in silico study identified a group of TTAGs and proteins as key regulators within a network of dysregulated genes in EC. We characterise relevant telomere/telomerase associated proteins (TTAPs) NOP10, NHP2, NOP56, TERF1, TERF2 and TERF2IP in the endometrium using quantitative polymerase chain reaction (qPCR) and immunohistochemistry (IHC). qPCR data demonstrated altered expression of multiple TTAPs; specifically, increased NOP10 (p = 0.03) and reduced NHP2 (p = 0.01), TERF2 (p = 0.01) and TERF2IP (p < 0.003) in EC relative to post-menopausal endometrium. Notably, we report reduced NHP2 in EC compared to post-menopausal endometrium in qPCR and IHC (p = 0.0001) data; with survival analysis indicating high immunoscore is favourable in EC (p = 0.0006). Our findings indicate a potential prognostic role for TTAPs in EC, particularly NHP2. Further evaluation of the prognostic and functional role of the examined TTAPs is warranted to develop novel treatment strategies.