Survival In Adenocarcinoma Research Articles

CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.

The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced CT, and integrated clinical characteristics to create a radiomics-clinical nomogram for prognostic prediction. In this retrospective study, data were collected from 124 PDAC patients treated surgically at a single center, from January 2017 to March 2023. Patients were categorized according to the Ki-67 expression rate. Radiomics features were extracted from arterial and portal venous phase CT images using 3D Slicer v5.0.3. A radiomics model was formulated and validated to predict the Ki-67 expression, and a nomogram combining clinical indicators and the radiomics model was developed to predict 1, 2 and 3year overall survival (OS). The optimal Ki-67 expression rate cutoff was identified as 50%, with significant OS differences. The developed radiomics model showed good predictive ability with area under the curves of 0.806 and 0.801 in the training and validation groups, respectively. High radiomics score, elevated carbohydrate antigen 19-9 (CA19-9), and receipt of adjuvant chemotherapy were identified as independent prognostic factors for OS. The radiomics-clinical nomogram accurately predicted 1, 2 and 3year OS in PDAC patients. The radiomics-clinical nomogram provides a non-invasive and efficient method for predicting Ki-67 expression and overall survival in PDAC patients, which could potentially guide clinical decision-making and improve patient outcomes.

Tertiary lymphoid structure signatures are associated with survival and immunotherapy response in lung adenocarcinoma

The presence of tertiary lymphoid structures (TLSs) has been correlated with improved prognosis and clinical outcomes in response to immunotherapy in certain solid tumors. However, the precise role of TLSs in lung adenocarcinoma (LUAD) remains unclear. Four datasets of LUAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The TLSs model was constructed using a multivariate Cox proportional hazards model. GO and KEGG analyses were performed to explore the biological process associated with the TLSs model. The ESTIMATE and CIBERSORT algorithms were employed to quantify immune infiltration status. TLSs signature genes (TSGs) were identified, including chemokine signature genes, TFH cell markers, TH1 cell and B cell markers, and a plasma cell marker. Diagnostic evaluations identified key genes with high diagnostic value, particularly among chemokine signature genes and TFH cells markers. Furthermore, high expression of CCL20 and IL1R2 was correlated with poorer outcomes, while other TSGs indicated more favorable prognoses. A novel TLSs score model was constructed, integrating 4 TSGs (SGPP2, MS4A1, IL1R2 and CCL20), which accurately predicted patient survival and was independently associated with prognosis. Additionally, the TLSs score served as a robust indicator for LUAD survival prediction, outperforming traditional staging systems. Comprehensive analyses of enriched pathways and immune cell infiltration patterns revealed that this score involved in metabolic processes and immune cell regulation. Furthermore, the TLSs score showed potential as an indicator of response to immunotherapy, with higher scores associated with reduced expression of immune checkpoint genes and poorer response rates. The TLSs score may serve as a predictor of prognosis and immunotherapeutic response in LUAD. These findings may offer new insights on the study of malignancy and personalized immunotherapy for LUAD patients.

Analysis of survival and prognostic factors in appendix adenocarcinoma and mucinous carcinoma.

This study aimed to compare mucinous carcinoma and adenocarcinoma of the appendix in terms of survival and investigate the risk factors influencing survival. The data for this study were retrieved from the SEER database (SEER Research Plus 17 registries). Patients diagnosed with appendix cancer between 2004 and 2019 were included. Demographic data, such as age, gender, marital status, and year of diagnosis, along with oncological variables like stage, surgery, chemotherapy, radiotherapy, and survival time, were extracted from the SEER database. Pathological subtypes were classified as adenocarcinoma (AC) and mucinous adenocarcinoma (MAC) based on the College of American Pathologists guidelines. Patients with other pathological subtypes or missing data were excluded from the study. This study included 4524 patients, with 2118 (46.8%) classified as AC and 2406 (53.2%) as MAC. There was no significant difference in mean age between AC and MAC groups (63.22 ± 14.30 vs. 59.46 ± 14.07, p = 0.483). AC was more common in males, while MAC was more prevalent in females (46.8% vs. 53.2%; 55.6% vs. 44.4%, p < 0.001, respectively). Married status was high in both groups (p = 0.001). While no difference was found in white race distribution, the black race was more prevalent in the AC group (57.1% vs. 42.9%, p < 0.001). Grade 1 tumors were more frequent in the AC group, whereas Grades 2 and 3 were more common in the MAC group (p < 0.001). Stages 1, 2, and 3 were more prevalent in the AC group, while the majority of MAC cases were at Stage 4. Surgery rates were higher in the AC group (98.6% vs. 96.4%, p < 0.001). Chemotherapy was used more frequently in the MAC group (50.9% vs. 40.6%, p < 0.001), while radiotherapy rates were similar in both groups (p = 0.498). The mean follow-up period was 55.70 ± 47.2months. Five- and ten-year survival rates for the MAC group were 64.4% and 50.2%, respectively, higher than the AC group's rates of 54.2% and 39.7% (p < 0.001). The overall risk of mortality was 1.4 times higher in the AC group compared to the MAC group (p < 0.001, HR: 1.377 [CI 95% 1.259-1.507]). While adenocarcinomas and mucinous adenocarcinomas have similar incidences, non-metastatic adenocarcinomas were more frequently observed. In contrast, mucinous adenocarcinomas often exhibited distant metastases. Nevertheless, the survival rate was higher in mucinous adenocarcinomas.

The X-Linked Tumor Suppressor TSPX Regulates Genes Involved in the EGFR Signaling Pathway and Cell Viability to Suppress Lung Adenocarcinoma.

Background: TSPX is an X-linked tumor suppressor that was initially identified in non-small cell lung cancer (NSCLC) cell lines. However, its expression patterns and downstream mechanisms in NSCLC remain unclear. This study aims to investigate the functions of TSPX in NSCLC by identifying its potential downstream targets and their correlation with clinical outcomes. Methods: RNA-seq transcriptome and pathway enrichment analyses were conducted on the TSPX-overexpressing NSCLC cell lines, A549 and SK-MES-1, originating from lung adenocarcinoma and squamous cell carcinoma subtypes, respectively. In addition, comparative analyses were performed using the data from clinical NSCLC specimens (515 lung adenocarcinomas and 502 lung squamous cell carcinomas) in the Cancer Genome Atlas (TCGA) database. Results: TCGA data analysis revealed significant downregulation of TSPX in NSCLC tumors compared to adjacent non-cancerous tissues (Wilcoxon matched pairs signed rank test p < 0.0001). Notably, the TSPX expression levels were inversely correlated with the cancer stage, and higher TSPX levels were associated with better clinical outcomes and improved survival in lung adenocarcinoma, a subtype of NSCLC (median survival extended by 510 days; log-rank test, p = 0.0025). RNA-seq analysis of the TSPX-overexpressing NSCLC cell lines revealed that TSPX regulates various genes involved in the cancer-related signaling pathways and cell viability, consistent with the suppression of cell proliferation in cell culture assays. Notably, various potential downstream targets of TSPX that correlated with patient survival (log-rank test, p = 0.016 to 4.3 × 10-10) were identified, including EGFR pathway-related genes AREG, EREG, FOSL1, and MYC, which were downregulated. Conclusions: Our results suggest that TSPX plays a critical role in suppressing NSCLC progression by downregulating pro-oncogenic genes, particularly those in the EGFR signaling pathway, and upregulating the tumor suppressors, especially in lung adenocarcinoma. These findings suggest that TSPX is a potential biomarker and therapeutic target for NSCLC management.

Neural invasion severity is a strong predictor of local recurrence in pancreatic ductal adenocarcinoma.

In pancreatic ductal adenocarcinoma, neural invasion is being increasingly recognized as an unfavorable predictor of patient outcomes. Neural invasion severity seems to have a stronger clinical impact on patient prognosis than neural invasion status alone. Therefore, this study aims to assess the impact of severity of neural invasion on overall survival and disease-free survival in pancreatic ductal adenocarcinoma. To assess the impact of intrapancreatic neural invasion severity, tumor specimens resected from patients with pancreatic ductal adenocarcinoma between 2007 and 2014 were systematically re-evaluated, and neural invasion severity was determined using the standardized neural invasion severity score. In our cohort (n= 216), an increased neural invasion severity score was associated with markedly shorter overall survival in pancreatic head ductal adenocarcinoma (neural invasion severity score low: 22.8months vs neural invasion severity score high: 17.6months: P= .001). An external European validation cohort confirmed these results and showed significantly better survival of patients with lower neural invasion (20.5 vs 15.4months, P= .026). The disease-free survival time was also substantially decreased in patients with pancreatic head pancreatic ductal adenocarcinoma and increased neural invasion severity (neural invasion severity score low: 19.1months vs neural invasion severity score high: 10.4months; P= .004). Moreover, the neural invasion severity score was an important independent factor influencing overall survival (hazards ratio 1.024, P= .04) and disease-free survival (hazards ratio 1.03, P= .01) using an adjusted Cox proportional hazards model. Importantly, higher neural invasion severity score leads to significantly more and earlier local recurrence than to distant tumor recurrence. Neural invasion severity is a powerful independent factor influencing overall survival and local recurrence in patients with pancreatic ductal adenocarcinoma. Therefore, individuals with high neural invasion severity score values should be regarded as a specific subgroup of pancreatic ductal adenocarcinoma patients and may benefit from more tailored postoperative oncologic therapy.

Bayesian analysis of competing risk models with high dimensional covariates with an application to adenocarcinoma survival data

This paper analyses competing risk models with high dimensional covariates when the number of observations is comparatively quite small. This gives rise to a very typical situation where most statistical estimates become unstable and non-unique. Thus dimension reduction by carrying out variable selection becomes a very imperative part of the study. This is performed using both classical and Bayesian tools. Lifetimes under each risk is assumed to follow either the Weibull or the exponential distribution and a total of four models is formed using a combination of these risks. Bayesian analysis of the resulting four models are performed via Markov chain Monte Carlo methods. A real life application is provided for adenocarcinoma micro-array data. Finally, model selection is carried out using deviance information criterion.

Comprehensive Overview of Molecular, Imaging, and Therapeutic Challenges in Rectal Mucinous Adenocarcinoma.

Rectal cancer is one of the most frequent malignancies worldwide. The most common histological type is adenocarcinoma, followed by mucinous adenocarcinoma. The outcome is less favorable for the mucinous type, yet the treatment course is the same. The aim of this systematic literature review is to assess existing information in order to improve survival in rectal mucinous adenocarcinoma (RMA) and establish a starting point for future research. A systematic search of PubMed, Google Scholar, and Web of Science online libraries was performed in October 2024, evaluating studies regarding clinicopathological and genetic features in connection with targeted treatment and survival outcomes in RMA, using the terms "rectal cancer", "rectum", "mucinous adenocarcinoma", or a combination of the terms. We selected 23 studies, 10 of them regarding the diagnostic implications and 13 discussing the treatment strategies and prognosis of this histological subtype. There were six studies addressing the imaging aspects, highlighting the distinct features of mucinous histology in MRI. The molecular specifics were detailed in four studies, outlining the molecular footprint. The prognosis and treatment course were addressed in 12 studies. The inflammation index prognosis, complete response to neoadjuvant chemotherapy, and surgical aspects were addressed individually in each study. We encapsulated the molecular and clinicopathological characteristics of RMA, as well as diagnostic and treatment approaches, to establish a baseline of references for the benefit of daily practice and further research.

HMGA2 Expression Predicts Subtype, Survival, and Treatment Outcome in Pancreatic Ductal Adenocarcinoma.

To establish HMGA2 as a marker of basal-like disease in pancreatic ductal adenocarcinoma (PDAC) and explore its use as a biomarker for prognosis and treatment resistance. We identified high expression of HMGA2 in basal PDAC cells in a scRNAseq Atlas of 172 patient samples. We then analyzed HMGA2 expression, along with expression of the classical marker GATA6, in a cohort of 580 PDAC samples with multiplex immunohistochemistry. We further supplemented these data with an additional 30 diverse patient samples and multiple independent single-cell RNAseq databases. We found that expression of HMGA2, but not previously described basal markers CK5 or CK17, predicted overall survival in our cohort. Combining HMGA2 and GATA6 status allowed for identification of two key study groups: an HMGA2+/GATA6- cohort with worse survival, low tumor-infiltrating CD8+ T cells, increased FAP+ fibroblasts, and poorer response to gemcitabine-based chemotherapies (n=94, median survival=11.2 months post-surgery); and an HMGA2-/GATA6+ cohort with improved survival, increased CD8+ T-cell infiltrate, decreased FAP+ fibroblasts, and improved survival with gemcitabine-based chemotherapy (n=198, median survival=21.7 months post-surgery). HMGA2 was also prognostic for overall survival in RNA sequencing from an independent cohort. IHC stratification of primary tumors by HMGA2 and GATA6 status in pancreatic cancer is associated with differential outcomes, survival following chemotherapy, and tumor microenvironments. As a nuclear marker for basal disease, HMGA2 complements GATA6 to identify disease subtypes in PDAC.

A Simple Morphometric Analysis of Preoperative Therapy Response for Esophageal Adenocarcinoma.

Histologic assessment of tumor regression grade (TRG) on esophagogastrectomy specimens after neoadjuvant therapy is an excellent predictor of local recurrence rate and long-term survival in esophageal adenocarcinomas. Although several grading systems exist globally, the modified Ryan system suggested by the College of American Pathologists (CAP) is widely used in North America. Most systems rely on quantitative percentage estimation of the residual tumor with or without additional qualitative descriptors, which is relatively subjective with poor interobserver agreement. To test a morphometric-based approach using the microscopic objective lens to estimate the size of the largest focus of the residual tumor. A total of 69 esophageal specimens post neoadjuvant therapy were evaluated. Tumor size was morphometrically determined by the microscopic field, using an Olympus microscope with ×10/×22 eyepieces. Residual viable tumor was categorized into 4 groups, using ×2, ×4, and ×10 objectives: less than or equal to an ×10 field; larger than an ×10 field but less than or equal to an ×4 field; larger than an ×4 field but less than an ×2 field; and larger than or equal to an ×2 field. Morphometric measurements significantly correlated with the CAP treatment effect scores. There was no significant difference in overall survival between larger than or equal to ×2 and ×2 to ×4 groups; however, a 3-tier system (TRG1: ≤ ×10, TRG2: > ×10 and ≤ ×4, and TRG3: > ×4) showed significant survival differences (P = .01). Significant differences in the percentage of lymphovascular and perineural invasion, advanced TNM stage, and lymph node metastasis were identified among the 3 groups. The proposed 3-tier morphometric approach based on microscopic field size is a simple and easy-to-use method, which helps stratify patients into 3 groups with distinct histopathologic features and overall survival.

Elevated Expression of Cell Adhesion, Metabolic, and Mucus Secretion Gene Clusters Associated with Tumorigenesis, Metastasis, and Poor Survival in Pancreatic Ductal Adenocarcinoma.

Technological advances in identifying gene expression profiles are being applied to study an array of cancers. The goal of this study was to identify differentially expressed genes in pancreatic ductal adenocarcinoma (PDAC) and examine their potential role in tumorigenesis and metastasis. The transcriptomic profiles of PDAC and non-tumorous tissue samples were derived from the gene expression omnibus (GEO), which is a public repository. The GEO2R tool was used to further derive differentially expressed genes from those profiles. In this study, a total of 68 genes were derived from upregulated PDAC genes in three or more transcriptomic profiles and were considered PDAC gene sets. The identified PDAC gene sets were examined in the molecular signatures database (MSigDB) for ontological investigation, which revealed that these genes were involved in the extracellular matrix and associated with the cell adhesion process in PDAC tumorigenesis. The gene set enrichment analysis showed greater enrichment scores for the gene sets. Moreover, the identified gene sets were examined for protein-protein interaction using the STRING database. Based on functional k-means clustering, the following three functional cluster groups were identified in this study: extracellular matrix/cell adhesion, metabolic, and mucus secretion-related protein groups. The receiver operating characteristic (ROC) curve revealed greater specificity and sensitivity for these cluster genes in predicting PDAC tumorigenesis and metastases. In addition, the expression of the cluster genes affects the overall survival rate of PDAC patients. Using the cancer genome atlas (TCGA) database, the associations between expression levels and clinicopathological features were validated. Overall, the genes identified in this study appear to be critical in PDAC development and can serve as potential diagnostic and prognostic targets for pancreatic cancer treatment.

Pre-Surgical Endoscopic Biopsies Are Representative of Esophageal and Esophago-Gastric Junction Adenocarcinoma Histologic Classes and Survival Risk.

Background and Objectives: The Esophageal Adenocarcinoma Study Group Europe (EACSGE) recently proposed a granular histologic classification of esophageal-esophago-gastric junctional adenocarcinomas (EA-EGJAs) based on the study of naïve surgically resected specimens that, when combined with the pTNM stage, is an efficient indicator of prognosis, molecular events, and response to treatment. In this study, we compared histologic classes of endoscopic biopsies taken before surgical resection with those of the surgical specimen, to evaluate the potential of the EACSGE classification at the initial diagnostic workup. Methods: A total of 106 EA-EGJA cases with available endoscopic biopsies and matched surgical resection specimens were retrieved from five Italian institutions. Histologic classification was performed on all specimens to identify well-differentiated glandular adenocarcinoma (WD-GAC), poorly differentiated glandular adenocarcinoma (PD-GAC), mucinous muconodular carcinoma (MMC), infiltrative mucinous carcinoma (IMC), diffuse desmoplastic carcinoma, diffuse anaplastic carcinoma (DAC), and mixed subtypes. Related risk subgroups (low-risk versus high-risk) were also assessed. The correlations of histologic classes and risk subgroups between diagnostic biopsies and surgical resection specimens were explored with Spearman's correlation test. Sensitivity, specificity, accuracy, positive predictive value, negative predictive value, true positives, true negatives, false positives, and false negatives were also calculated. Results: A strong positive correlation between biopsies and surgical specimens occurred for both histologic classes (coefficient: 0.75, p < 0.001) and risk subgroups (coefficient: 0.65, p < 0.001). The highest sensitivities and specificities were observed for MMC, IMC, and DAC (100% and 99% for all), followed by WD-GAC (sensitivity 91%, specificity 79%) and PD-GAC (sensitivity 722%, specificity 86%). The low-risk and high-risk groups presented a sensitivity and specificity of 89% and 76% (low-risk) and 76% and 89% (high-risk). Conclusions: The EACSGE histologic classification of EA-EGJAs and associated prognostic subgroups can be reliably assessed on pre-operative diagnostic biopsies. Further studies on larger and more representative cohorts of EA-EGJAs will allow us to validate our findings and confirm if the EA-EGJA biopsy histomorphology and clinical TNM staging will be as efficient as the surgical specimen histomorphology and pTNM in predicting patient prognoses and tailoring personalized therapeutic approaches.

General anesthesia induces acute cell-free DNA methylation changes in peripheral blood.

Short-term and long-term adverse events could occur after general anesthesia (GA) and the specific mechanism driving these effects has not yet been well-characterized. In this study, we aimed to evaluate the global effect of GA on DNA methylation in the cell-free DNA (cfDNA) of surgical lung-nodule patients. This large retrospective cohort study enrolled 1,006 surgical lung nodule patients (529 pre-anesthesia, and 477 post-anesthesia). Methylation profiles of the cfDNA isolated from plasma were analyzed by targeted bisulfite sequencing using an enrichment panel covering 12,899 biologically informative methylation regions and 105,844 CpG sites. By comparing the pre-anesthesia to the post-anesthesia group, a total of 4,562 differentially methylated regions (DMRs) were identified as GA-induced DMRs. Pathway enrichment analysis annotated with cellular processes including pattern specification process, head/heart/bone/tissues development and morphogenesis pathways, cell-adhesion, extra-cellular matrix (ECM) remodeling pathways, and signaling pathways including PI3K-AKT pathway, Ca2+ dependent pathway and RAS/extracellular signal-regulated kinase (RAS/ERK) signaling pathway. Prediction models using 20 DMR markers were derived using Random Forest, which could accurately predict biochemical indicators for post-operative abnormal coagulation function including activated-partial-thromboplastin-time [APTT, area under curve (AUC) 0.81], international normalized ratio (INR, AUC 0.87), D-dimer (AUC 0.82), neutrophil (AUC 0.84) and monocyte (AUC 0.79). Low methylation level in one of the top DMR markers, cg02032606 (DLX-4 gene), was found to be associated with worse overall survival in both lung adenocarcinoma and squamous carcinoma patients. This study demonstrated that GA could result in acute DNA methylation changes, which were associated with tissue damage and repair responses. These GA-induced methylation changes were associated with postoperative coagulation functions and could serve as a promising predictive biomarker for coagulation disorders after surgery.

Sex-based differences in CEACAM5 expression in lung cancer.

Carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) is expressed in 20-25% of non-small cell lung cancer (NSCLC) and there is interest in CEACAM5 as a biomarker given its potential for blood-based detection and investigational study as a drug target. Increased expression of CEACAM5 has been observed in semi-solid lung adenocarcinoma lesions, which have an increased prevalence in women and never smokers. Given this association, sex-based differences in CEACAM5 were evaluated. The Cancer Genome Atlas (TCGA) data on CEACAM5 expression in NSCLC tumors (n=994) in women (n=398) and men (n=596) were analyzed for differences in expression of CEACAM5 based on sex and histologic subtypes of adenocarcinoma and for correlations with overall survival (OS). Among all stages of NSCLC, mean expression of CEACAM5 was 143.3 fragments per kilobase of transcript per million (FPKM) with differences observed between female and male patients (194.5 vs. 109.2 FPKM, P<0.0001) and between adenocarcinoma and squamous cell carcinoma (239.3 vs. 46.2 FPKM, P<0.0001). Differences persisted among combined sex and histology subgroups. High CEACAM5 was not predictive of survival in NSCLC or adenocarcinoma overall, but was associated with worse survival among stage I female patients with adenocarcinoma (5-year OS CEACAM5 high =33% vs. low =64%, log-rank P=0.008). Higher levels of CEACAM5 expression are observed in NSCLC tumors in female patients and adenocarcinoma histology. High CEACAM5 expression in lung adenocarcinoma is associated with worse survival among female patients. The biologic impact of sex on CEACAM5 as a biomarker warrants further study.

Prognostic factors in localized pancreatic ductal adenocarcinoma after neoadjuvant therapy and resection: a systematic review and Meta-Analysis.

Prognostic markers for overall survival (OS) in resected pancreatic ductal adenocarcinoma (PDAC) are well-established but remain unclear following neoadjuvant therapy (NAT). This systematic review and meta-analysis aimed to determine factors associated with OS following NAT in resected PDAC. The PubMed, Embase, Scopus, Web of Science, and Cochrane CENTRAL databases were systematically searched from inception till May 2024. Studies that reported univariable and multivariable hazard ratios (HRs) were included if patients underwent NAT and resection for localized PDAC. Study quality assessment was performed using the Newcastle-Ottawa scale. Meta-analysis was performed using generic inverse-variance random-effects models. Among 2,208 unique articles identified by the search, 92 were included in the meta-analysis. Eighty-five of these were of 'good' and 7 of 'poor' quality. The NAT regimen was described in 84 studies, of which 62 included patients treated with FOLFIRINOX (FFX). Margin status, nodal disease, AJCC T-stage, and normalization of CA19-9 after NAT were prognostic for OS, while age, sex, perineural invasion, baseline tumor size, and baseline CA19-9 were not. The test for subgroup differences between ypN-substages was not significant in the multivariable model. Neoadjuvant FFX was associated with better survival than other regimens. This meta-analysis identified margin status, nodal disease, AJCC T-stage, and normalization of CA19-9 after NAT as prognostic factors for OS in patients with resected localized PDAC following NAT.

Construction of a novel lipid drop-mitochondria-associated genetic profile for predicting the survival and prognosis of lung adenocarcinoma

BackgroundLung adenocarcinoma (LUAD) is one of the most common malignant tumors. Although several treatments have been proposed, the long-term prognosis of this cancer is poor. Lipid droplets and mitochondria are important organelles that regulate energy metabolism in cells and are postulated to promote the occurrence and progression of tumors. However, few risk prediction models have been constructed based on lipid drop-mitochondria-related genes (LMRGs).MethodsIn this study, we constructed a lipid drop-mitochondrial (LD-M) risk score model based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Biological functions and clinical benefits associated with the various risk scores were analyzed using R software, GraphPad Prism 9, and the online database system.ResultsAn LD-M risk score model comprising ABLIM3, AK4, CAV2, CPS1, CYP24A1, DLGAP5, FGR, and SH3BP5, was developed and its predictive power was validated. The risk score was closely associated with the cell cycle. Immunophenoscore (IPS) and Tumor immune dysfunction and exclusion (TIDE) results demonstrated that the low-risk group was more sensitive to immunotherapy. Drug sensitivity analysis indicated that BMS-754807, ZM447439, SB216763, and other drugs had lower IC50 values in the low-risk group.ConclusionOur results suggest that the LD-M risk score is an effective prognostic indicator for individualized treatment of LUAD.

Abstract B017: Discovery of cancer-specific small RNAs using a new unbiased analysis of cohort sequence data

Abstract It is well-established that small RNAs such as microRNAs can have important roles as oncogenes or tumor suppressors. The majority of studies of small RNAs in cancer have focused on examining the often subtle deregulation of specific, well-characterized molecules, aiming to understand their role in tumorigenesis. However, these efforts have predominantly concentrated on known, well-annotated RNA sequences, potentially overlooking novel, cancer-specific molecules. In this study, we sought to apply a new computational approach to uncover small RNA molecules that are uniquely associated with cancer and are completely absent from all non- cancerous tissues. To achieve this, we developed an unbiased approach that can detect cancer- specific sequences even if they are lowly abundant, do not overlap with existing genome annotations and even if they do not map to the human reference genome. We applied our framework to hundreds of small RNA-seq samples across a diverse range of cancer types from two large-scale public resources: The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Through this comprehensive analysis, we identified a series of small RNA molecules that are exclusively present in tumor samples and completely absent in adjacent normal tissues across multiple cancer types. Furthermore, these molecules were not detected in a large cohort comprising over 2,500 non-cancerous public samples, underscoring their specificity to cancerous conditions. Some of these molecules are also associated with different patient metadata. For example, one of these candidates exhibited significant correlation with poor patient survival in both Lung Adenocarcinoma and Endometrial Carcinoma within both the TCGA and CPTAC datasets. The discovery of such cancer-specific small RNAs holds immense potential for clinical applications. These molecules could serve as highly specific diagnostic and prognostic biomarkers, aiding in the early detection and stratification of cancers. Moreover, their unique presence in cancer cells, positions them as promising targets for the development of novel therapeutic interventions. In summary, our findings highlight the importance of exploring the full spectrum of small RNAs in cancer research. By moving beyond the constraints of known annotations, we have uncovered previously unknown molecules that could improve cancer diagnostics, prognostics, and treatment. Citation Format: Panagiotis Kalogeropoulos, Maria Alejandra Ulloa, Marc Friedländer. Discovery of cancer-specific small RNAs using a new unbiased analysis of cohort sequence data [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: RNAs as Drivers, Targets, and Therapeutics in Cancer; 2024 Nov 14-17; Bellevue, Washington. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(11_Suppl):Abstract nr B017.

Peripheral Eosinophil Count May Be the Prognostic Factor for Overall Survival in Patients with Pancreatic Ductal Adenocarcinoma Undergoing Surgical Treatment.

(1) Background: The importance of total eosinophil count in peripheral blood (EOS) as a type 2 inflammation marker is known to be fundamental in asthma, chronic sinusitis, and vasculitis. In cancer, despite their questionable antiproliferative effect, their role remains unclear. Our purpose was to describe the relationship between baseline blood EOS and overall survival (OS) in pancreatic ductal adenocarcinoma (PDAC) patients. (2) Methods: We retrospectively analyzed data from 137 adult patients who underwent surgical treatment for pancreatic ductal adenocarcinoma (PDAC) between the years 2012 and 2019. Patients with no recent history of systemic steroid use and without intraoperative metastases were included. Patients were categorized into two groups based on EOS (≥0.1 G/l and <0.1 G/l). Survival outcomes were analyzed using Cox proportional hazards regression models. (3) Results: According to EOS and PDAC stage, median OS values were as follows: in stage I-III, EOS ≥ 0.1 G/l group: 14.5 months, in stage I-III, EOS < 0.1 G/l group: 8.0 months, in stage IV, EOS ≥ 0.1 G/l group: 7.0 months, and in stage IV, EOS < 0.1 G/l group: 5.0 months. EOS < 0.1 G/l (vs. ≥0.1 G/l) was an independent prognostic factor for OS in both the uni- and multivariate Cox regression, respectively (HR = 1.48, p = 0.035 and HR = 1.57, p = 0.021). (4) Conclusions: Peripheral eosinophilia seems to be a potential independent prognostic factor. Further studies are necessary to confirm this hypothesis, since our findings suggest that type 2 inflammation may be the factor directly or indirectly lengthening the survival of patients with PDAC.

Machine learning model for early prediction of survival in gallbladder adenocarcinoma: A comparison study

The prognosis for gallbladder adenocarcinoma (GBAC), a highly malignant cancer, is not good. In order to facilitate individualized risk stratification and improve clinical decision-making, this study set out to create and validate a machine learning model that could accurately predict early survival outcomes in GBAC patients. Five models—RSF, Cox regression, GBM, XGBoost, and Deepsurv—were compared using data from the SEER database (2010–2020). The dataset was divided into training (70 %) and validation (30 %) sets, and the C-index, ROC curves, calibration curves, and decision curve analysis (DCA) were used to assess the model's performance. At 1, 2, and 3-year survival intervals, the RSF model performed better than the others in terms of calibration, discrimination, and clinical net benefit. The most important predictor of survival, according to SHAP analysis, is AJCC stage. Patients were divided into high, medium, and low-risk groups according to RSF-derived risk scores, which revealed notable variations in survival results. These results demonstrate the RSF model's potential as an early survival prediction tool for GBAC patients, which could enhance individualized treatment and decision-making.

A Novel Gene Signature Based on Immune Cell Infiltration Landscape Predicts Prognosis in Lung Adenocarcinoma Patients.

The tumor microenvironment (TME) is created by the tumor and dominated by tumor-induced interactions. Long-term survival of lung adenocarcinoma (LUAD) patients is strongly influenced by immune cell infiltration in TME. The current article intends to construct a gene signature from LUAD ICI for predicting patient outcomes. For the initial phase of the study, the TCGA-LUAD dataset was chosen as the training group for dataset selection. We found two datasets named GSE72094 and GSE68465 in the Gene Expression Omnibus (GEO) database for model validation. Unsupervised clustering was performed on the training cohort patients using the ICI profiles. We employed Kaplan-Meier estimators and univariate Cox proportional-hazard models to identify prognostic differentially expressed genes in immune cell infiltration (ICI) clusters. These prognostic genes are then used to develop a LASSO Cox model that generates a prognostic gene signature. Validation was performed using Kaplan-Meier estimation, Cox, and ROC analysis. Our signature and vital immune-relevant signatures were analyzed. Finally, we performed gene set enrichment analysis (GSEA) and immune infiltration analysis on our finding gene signature to further examine the functional mechanisms and immune cellular interactions. Our study found a sixteen-gene signature (EREG, HPGDS, TSPAN32, ACSM5, SFTPD, SCN7A, CCR2, S100P, KLK12, MS4A1, INHA, HOXB9, CYP4B1, SPOCK1, STAP1, and ACAP1) to be prognostic based on data from the training cohort. This prognostic signature was certified by Kaplan-Meier, Cox proportional-hazards, and ROC curves. 11/15 immune-relevant signatures were related to our signature. The GSEA results indicated our gene signature strongly correlates with immune-related pathways. Based on the immune infiltration analysis findings, it can be deduced that a significant portion of the prognostic significance of the signature can be attributed to resting mast cells. We used bioinformatics to determine a new, robust sixteen-gene signature. We also found that this signature's prognostic ability was closely related to the resting mast cell infiltration of LUAD patients.

TGFB2 mRNA Levels Prognostically Interact with Interferon-Alpha Receptor Activation of IRF9 and IFI27, and an Immune Checkpoint LGALS9 to Impact Overall Survival in Pancreatic Ductal Adenocarcinoma

The treatment of pancreatic ductal adenocarcinoma (PDAC) is an unmet challenge, with the median overall survival rate remaining less than a year, even with the use of FOLFIRINOX-based therapies. This study analyzed archived macrophage-associated mRNA expression using datasets deposited in the UCSC Xena web platform to compare normal pancreatic tissue and PDAC tumor samples. The TGFB2 gene exhibited low mRNA expression levels in normal tissue, with less than one TPM. In contrast, in tumor tissue, TGFB2 expression levels exhibited a 7.9-fold increase in mRNA expression relative to normal tissue (p &lt; 0.0001). Additionally, components of the type-I interferon signaling pathway exhibited significant upregulation of mRNA levels in tumor tissue, including Interferon alpha/beta receptor 1 (IFNAR1; 3.4-fold increase, p &lt; 0.0001), Interferon regulatory factor 9 (IRF9; 4.2-fold increase, p &lt; 0.0001), Signal transducer and activator of transcription 1 (STAT1; 7.1-fold increase, p &lt; 0.0001), and Interferon Alpha Inducible Protein 27 (IFI27; 66.3-fold increase, p &lt; 0.0001). We also utilized TCGA datasets deposited in cBioportal and KMplotter to relate mRNA expression levels to overall survival outcomes. These increased levels of mRNA expression were found to be prognostically significant, whereby patients with high expression levels of either TGFB2, IRF9, or IFI27 showed median OS times ranging from 16 to 20 months (p &lt; 0.01 compared to 72 months for patients with low levels of expression for both TGFB2 and either IRF9 or IFI27). Examination of the KMplotter database determined the prognostic impact of TGFB2 mRNA expression levels by comparing patients expressing high versus low levels of TGFB2 (50th percentile cut-off) in low macrophage TME. In TME with low macrophage levels, patients with high levels of TGFB2 mRNA exhibited significantly shorter OS outcomes than patients with low TGFB2 mRNA levels (Median OS of 15.3 versus 72.7 months, p &lt; 0.0001). Furthermore, multivariate Cox regression models were applied to control for age at diagnosis. Nine genes exhibited significant increases in hazard ratios for TGFB2 mRNA expression, marker gene mRNA expression, and a significant interaction term between TGFB2 and marker gene expression (mRNA for markers: C1QA, CD74, HLA-DQB1, HLA-DRB1, HLA-F, IFI27, IRF9, LGALS9, MARCO). The results of our study suggest that a combination of pharmacological tools can be used in treating PDAC patients, targeting both TGFB2 and the components of the type-I interferon signaling pathway. The significant statistical interaction between TGFB2 and the nine marker genes suggests that TGFB2 is a negative prognostic indicator at low levels of the IFN-I activated genes and TAM marker expression, including the immune checkpoint LGALS9 (upregulated 16.5-fold in tumor tissue; p &lt; 0.0001).