BACKGROUND: The unfolded protein response (UPR) is associated with immune cells that regulate the biological behavior of tumors. This article aims to combine UPR-associated genes with immune cells to find a prognostic marker and to verify its connection to the UPR.
METHODS: Univariate cox analysis was used to screen prognostically relevant UPRs and further screened for key UPRs among them by machine learning. ssGSEA was used to calculate immune cell abundance. Univariate cox analysis was used to screen for prognostically relevant immune cells. Multivariate cox analysis was used to calculate UPR_score and Tumor Immune Microenvironment score (TIME_score). WGCNA was used to screen UPR-Immune-related (UI-related) genes. Consensus clustering analysis was used to classify patients into molecular subtype. Based on the UI-related genes, we classified colon adenocarcinoma (COAD) samples by cluster analysis. Single-cell analysis was used to analyze the role of UI-related genes. We detected the function of TIMP1 by cell counting and transwell. Immunoblotting was used to detect whether TIMP1 was regulated by key UPR genes.
RESULTS: Combined UPR-related genes and immune cells can determine the prognosis of COAD patients. Cluster analysis showed that UI-related genes were associated with clinical features of COAD. Single-cell analysis revealed that UI-related genes may act through stromal cells. We defined three key UI-related genes by machine learning algorithms. Finally, we found that TIMP1, regulated by key genes of UPR, promoted colon cancer proliferation and metastasis.
CONCLUSIONS: We found that TIMP1 was a prognostic marker and experimentally confirmed that TIMP1 was regulated by key genes of UPR.

Human T cell lymphotropic virus type 1 (HTLV-1) is a retrovirus that infects lymphocytes and causes severe diseases. HTLV-1 proviral load (PVL), i.e., the number of host cells that carry HTLV-1 proviral DNA integrated into their genome, can be measured in peripheral blood mononuclear cells (PBMCs) using quantitative polymerase chain reaction. In this narrative review, we discuss the usefulness of HTLV-1 PVL quantification and share our experience acquired during more than 30 years of follow-up of people living with HTLV-1 in the UK. Patients with HTLV-1-associated myelopathy have higher PVL than those with asymptomatic infection. This is consistent across studies in different countries. High PVL predates symptom onset for both inflammatory and proliferative diseases. High PVL is essential but not sufficient for the development of HTLV-1-associated diseases. Therefore, PVL quantification can be used to support the care of people living with HTLV-1 by identifying those most at risk of HTLV-1-associated diseases.

BACKGROUND: Ki-67 immunostaining is commonly used in neuroendocrine tumors to estimate the proliferative index and for grading. This study investigates its association with the invasiveness of follicular-derived thyroid carcinomas (TCs).
METHODS: A retrospective analysis of patients with TC at three McGill University teaching hospitals between January 2018 and November 2023 was conducted. The inclusion criteria included patients with malignant thyroid tumors and accessible Ki-67 LI data from final pathology specimens. The data collected included patient demographics, Ki-67 LI values, and different invasiveness attributes, such as molecular mutations, the histological subtype, lymphovascular invasion (LVI), extrathyroidal extension (ETE), and positive lymph nodes (LNs).
RESULTS: In total, 212 patients met the inclusion criteria, of which 80.7% were females and 19.3% were males. The Ki-67 LI ranged from 1% to 30%, with the majority of the cases within the range of 1-15%. A significant association was observed between higher Ki-67 LI and high-risk histological subtypes of thyroid carcinoma (p < 0.001). Similarly, Ki-67 LI was significantly associated with LVI and positive LN metastasis (p < 0.001 and p = 0.036, respectively). However, no significant association was found between the Ki-67 LI and gene mutations or ETE (p = 0.133 and p = 0.190, respectively). Using percentiles to establish a cutoff, patients with a Ki-67 LI higher than 6.7 showed a higher likelihood of being associated with invasive features.
CONCLUSIONS: Elevated Ki-67 LI can serve as an indicator of aggressiveness in follicular-derived TC, especially when associated with distinct histological subtypes, LVI and positive LNs.

UNASSIGNED: Breast cancer is the most prevalent cancer among women worldwide and is a well-known cause for cancer mortality in females. COX-2 (cyclooxygenase) plays a vital role in development of some human cancers such as lung, colon and breast. It is a potent enzyme that is important for the conversion of arachidonic acid into prostaglandins. These prostaglandins mediate cellular proliferation, apoptosis and angiogenesis which contributes to carcinogenesis. Overexpression of COX-2 has been detected in several malignancies including breast cancer. COX-2 overexpression is regarded as a poor prognostic marker of breast cancer.The present study will aim to study the immunohistochemical expression of COX-2 in breast cancer and compare it with known histopathological parameters thus assessing its prognostic value.
UNASSIGNED: This will be an observational study conducted in the Department of Pathology, JNMC, Wardha (Sawangi). Radical mastectomy specimens will be studied for COX-2 expression by immunohistochemistry in patients diagnosed with breast carcinoma. COX-2 expression will be quantified as immunohistochemical score and results will be correlated with various histopathological parameters.
UNASSIGNED: The expected result of our study will suggest an association of COX-2 expression to the factors associated with poor prognosis in breast carcinoma. A positive correlation is expected between larger tumor size, positive lymph node status, higher T stage and N stage and lymphovascular invasion.
UNASSIGNED: Conclusions will be drawn from the obtained results of the immunohistochemical study by using COX-2- for detection of overexpression of COX-2 when evaluated with TNM staging, histological grading and molecular types of breast cancer.

A macroscopic perspective is indispensable for understanding the intricate relationship between deubiquitinases and tumorigenesis. Proteomics has been proposed as a viable approach for elucidating the complex role of deubiquitylation in cellular progression. Instead of studying the function of a single ubiquitinase, research on a deubiquitinase family with similar catalytic core(s) may provide a new perspective for the pathological understanding of cancer. The Ubiquitin C-terminal hydrolase L (UCHL) family consists of four members: UCHL1, UCHL3, UCHL5, and BRAC1 associated protein-1 (BAP1), and they have been implicated in tumorigenesis and metastasis. Some members are considered hallmarks of intracranial lesions, colon cancer, chromatin remodeling, and histone stability. The present study uncovered an unknown correlation between the UCHL family and renal cancer. We discovered that UCHLs exhibit diverse regulatory effects in renal cancer, establishing connections between the renal cancer and truncated gene mutations, mitochondrial energetic metastasis, immune cell infiltration, and chromosomal stability of UCHLs family. Notably, we found that the increase of UCHL5 expression in renal cancer cells decreases the antigen processing and presentation of RCC tumor-infiltrating B cells. Further research identified that the expression of UCHL5 in RCC tumors is correlated with transport proteins, which led us to find that the abundance of UCHL5 in the blood of late-stage renal cell cancer patients is upregulated from 18 ng/L to 500 ng/L. Therefore, we propose that the abundance of UCHL5 in patients\' blood can be a possible indicator of poor prognosis for renal cell cancer.

Hepatocellular carcinoma (HCC) is a challenging cancer with high mortality rates, limited predictability, and a lack of effective prognostic indicators. The relationship between small nucleolar RNAs (snoRNAs) and HCC is poorly understood. Based on the literature data, snoRNA studies were primarily focused on viral-related causes of HCC, such as Hepatitis B or C viruses (HBV or HCV). According to these studies, we selected four snoRNAs (snoRA12, snoRA47, snoRA80E, and snoRD126) for exploration in the context of non-viral-related causes, including non-alcoholic steatohepatitis (NASH), non-alcoholic fatty liver diseases (NAFLD), and alcohol steatohepatitis. The primary goal of this study was to gain a deeper understanding of how snoRNA expression affects patient outcomes and whether it can serve as a prognostic tool for non-viral HCC. We conducted a study on tissue samples from 35 HCC patients who had undergone resection at Pilsen University Hospital. SnoRA12, snoRA47, snoRA80E, and snoRD126 were studied by quantitative real-time PCR (qRT-PCR) in tumor and non-tumor adjacent tissue (NTAT) samples. Kaplan-Meier analysis was performed to assess the association of snoRNAs expression levels with patient outcomes: time to recurrence (TTR), disease-free survival (DFS) and overall survival (OS). In tumor tissues, snoRA12, snoRA47 and snoRA80E were upregulated, while snoRD-126 was downregulated compared to NTAT. Low expression of snoRA47 and snoRD126 in patients was associated with longer TTR and DFS. The individual expression of snoRA12 and snoRA80E did not show associations with TTR and DFS. However, a combination of medium expression of snoRD126 and snoRA80E was associated with longer TTR and DFS, while high and low expressions of the combined snoRA126 and snoRA80E showed no significant association with TTR, DFS, and OS. Conversely, a combination of high expression of snoRA12 and snoRD126 was associated with shorter TTR. In conclusion, the results indicate that snoRA47 and snoRD126 exhibit good prognostic power specifically for non-viral related HCC. Both snoRA47 and snoRD126 showed favorable prognostication in single and combined analysis when assessing patient outcomes. Also, in combination analysis, snoRA80E and snoRA12 showed favorable prognosis, but not alone.

UNASSIGNED: Current prognostic tools do not reliably and objectively identify children with pneumonia at risk of a severe or life-threatening episode. Heparin-binding protein (HBP) is a host immune protein that is released in response to infection. We hypothesized that measuring HBP concentrations at hospital admission could help risk-stratify children with pneumonia and identify those at higher risk of an adverse prognosis.
UNASSIGNED: We evaluated the prognostic accuracy of HBP for predicting in-hospital mortality among children with respiratory distress, and whether HBP could improve the accuracy of validated composite clinical severity scores.
UNASSIGNED: Of 778 Ugandan children under 5 years of age and presenting with clinically defined pneumonia, 60 (7.7%) died during hospital admission. HBP concentrations at presentation were significantly higher in children with fatal outcomes (median, 76 ng/mL [interquartile range {IQR}, 41-150]) compared to children who survived (median, 31 ng/mL [IQR, 18-57]) (P < .001). Children with HBP >41 ng/mL on admission had an elevated risk of death (hazard ratio, 5.3 [95% confidence interval {CI}, 2.9-9.5]; P < .0001). In receiver operating characteristic (ROC) curve analysis, HBP concentrations distinguished between fatal and nonfatal outcomes (area under the ROC curve, 0.75 [95% CI, .66-.84]) and significantly improved the prediction provided by the Respiratory Index of Severity in Children, a composite clinical severity score (P = .0026).
UNASSIGNED: Measuring HBP at presentation could help identify children at risk of severe and fatal pneumonia. Adding HBP to clinical scores could improve the recognition and triage of children with pneumonia at risk of death.

UNASSIGNED: Osteosarcoma primarily affects children and adolescents, with current clinical treatments often resulting in poor prognosis. There has been growing evidence linking programmed cell death (PCD) to the occurrence and progression of tumors. This study aims to enhance the accuracy of OS prognosis assessment by identifying PCD-related prognostic risk genes, constructing a PCD-based OS prognostic risk model, and characterizing the function of genes within this model.
UNASSIGNED: We retrieved osteosarcoma patient samples from TARGET and GEO databases, and manually curated literature to summarize 15 forms of programmed cell death. We collated 1621 PCD genes from literature sources as well as databases such as KEGG and GSEA. To construct our model, we integrated ten machine learning methods including Enet, Ridge, RSF, CoxBoost, plsRcox, survivalSVM, Lasso, SuperPC, StepCox, and GBM. The optimal model was chosen based on the average C-index, and named Osteosarcoma Programmed Cell Death Score (OS-PCDS). To validate the predictive performance of our model across different datasets, we employed three independent GEO validation sets. Moreover, we assessed mRNA and protein expression levels of the genes included in our model, and investigated their impact on proliferation, migration, and apoptosis of osteosarcoma cells by gene knockdown experiments.
UNASSIGNED: In our extensive analysis, we identified 30 prognostic risk genes associated with programmed cell death (PCD) in osteosarcoma (OS). To assess the predictive power of these genes, we computed the C-index for various combinations. The model that employed the random survival forest (RSF) algorithm demonstrated superior predictive performance, significantly outperforming traditional approaches. This optimal model included five key genes: MTM1, MLH1, CLTCL1, EDIL3, and SQLE. To validate the relevance of these genes, we analyzed their mRNA and protein expression levels, revealing significant disparities between osteosarcoma cells and normal tissue cells. Specifically, the expression levels of these genes were markedly altered in OS cells, suggesting their critical role in tumor progression. Further functional validation was performed through gene knockdown experiments in U2OS cells. Knockdown of three of these genes-CLTCL1, EDIL3, and SQLE-resulted in substantial changes in proliferation rate, migration capacity, and apoptosis rate of osteosarcoma cells. These findings underscore the pivotal roles of these genes in the pathophysiology of osteosarcoma and highlight their potential as therapeutic targets.
UNASSIGNED: The five genes constituting the OS-PCDS model-CLTCL1, MTM1, MLH1, EDIL3, and SQLE-were found to significantly impact the proliferation, migration, and apoptosis of osteosarcoma cells, highlighting their potential as key prognostic markers and therapeutic targets. OS-PCDS enables accurate evaluation of the prognosis in patients with osteosarcoma.

Colorectal cancer (CRC) remains a significant contributor to cancer-related mortality, emphasizing the critical need for identifying biomarkers that can improve clinical management and patient outcomes. In this retrospective study, we analyzed tumor samples from 25 patients with metastatic CRC, categorized based on long-term (> 50 months) or short-term (< 10 months) survival. Employing the PanCancer Immune Profile Panel, encompassing 770 genes, in the discovery dataset, we identified 54 differentially expressed genes (DEGs) within the tumor microenvironment of metastatic CRC. Validation of potential biomarkers was performed using two publicly available RNA-based sequencing datasets (TCGA 1 (n=371) and TCGA 2 (n=566)). Univariate COX regression unveiled that three significant biomarkers were associated with overall survival in CRC within the discovery dataset, which were SLC11A1 (hazard ratio (HR): 4.09, P=0.012), TNFSF11 (HR: 3.67, P=0.02), and MEF2C (HR: 0.34, P=0.037). Kaplan-Meier survival curve analyses confirmed the correlation between SLC11A1 expression and overall survival in CRC across the discovery set (P=0.0071) and the two independent datasets (TCGA 1 (P=0.0016) and TCGA 2 (P=0.025)). Receiver operating characteristic curve analysis demonstrated an area under the curve ranging from 0.64 to 0.76, with sensitivity of 59% to 87% and specificity of 60% to 73% for predicting CRC overall survival. Immunohistochemistry staining further validated the strong expression of SLC11A1 protein in CRC tumor cells, with high expression correlating with short-term survival. These findings suggest that SLC11A1 serves as a predictive biomarker for overall survival in CRC patients.

UNASSIGNED: The Geriatric Nutritional Risk Index (GNRI) indicates nutritional status based on serum albumin concentration and ideal body weight. Pretreatment GNRI has been suggested as a prognostic factor for various malignancies. However, little is known about the clinical value of GNRI for small-cell lung cancer (SCLC), especially in elderly patients.
UNASSIGNED: We retrospectively analyzed 53 elderly (≥71) patients with extensive-disease (ED) SCLC treated with first-line platinum-doublet chemotherapy in relation to the pretreatment GNRI level in a real-world setting.
UNASSIGNED: Thirty-six patients with a low GNRI (<92) had statistically poorer progression-free survival (PFS) and overall survival (OS) than 17 patients with a high GNRI (≥92) (median PFS=80 days vs. 133 days, respectively; p=0.002; median OS=123 days vs. 274 days, respectively; p=0.004). In a multivariate analysis, a low GNRI was also an independent poor prognostic factor for PFS [hazard ratio (HR)=0.396; 95% confidence interval (CI)=0.199-0.789; p=0.008] and OS (HR=0.295; 95%CI=0.143-0.608; p<0.001).
UNASSIGNED: The GNRI might be a predictive and prognostic marker in elderly patients with ED-SCLC treated with platinum-doublet chemotherapy.