Independent Prognostic Marker Research Articles

PARP1-DOT1L transcription axis drives acquired resistance to PARP inhibitor in ovarian cancer.

Poly (ADP-ribose) polymerase inhibitor (PARPi) resistance poses a significant challenge in ovarian carcinoma (OC). While the role of DOT1L in cancer and chemoresistance is acknowledged, its specific role in PARPi resistance remains unclear. This study aims to elucidate the molecular mechanism of DOT1L in PARPi resistance in OC patients. This study analyzed the expression of DOT1L in PARPi-resistant cell lines compared to sensitive ones and correlated it with clinical outcomes in OC patients. Comprehensive in vitro and in vivo functional experiments were conducted using cellular and mouse models. Molecular investigations, including RNA sequencing, chromatin immunoprecipitation (ChIP) and Cleavage Under Targets and Tagmentation (CUT&Tag) assays, were employed to unravel the molecular mechanisms of DOT1L-mediated PARPi resistance. Our investigation revealed a robust correlation between DOT1L expression and clinical PARPi resistance in non-BRCA mutated OC cells. Upregulated DOT1L expression in PARPi-resistant tissues was associated with diminished survival in OC patients. Mechanistically, we identified that PARP1directly binds to the DOT1L gene promoter, promoting transcription independently of its enzyme activity. PARP1 trapping induced by PARPi treatment amplified this binding, enhancing DOT1L transcription and contributing to drug resistance. Sequencing analysis revealed that DOT1L plays a crucial role in the transcriptional regulation of PLCG2 and ABCB1 via H3K79me2. This established the PARP1-DOT1L-PLCG2/ABCB1 axis as a key contributor to PARPi resistance. Furthermore, we discovered that combining a DOT1L inhibitor with PARPi demonstrated a synergistic effect in both cell line-derived xenograft mouse models (CDXs) and patient-derived organoids (PDOs). Our results demonstrate that DOT1L is an independent prognostic marker for OC patients. The PARP1-DOT1L/H3K79me2-PLCG2/ABCB1 axis is identified as a pivotal contributor to PARPi resistance. Targeted inhibition of DOT1L emerges as a promising therapeutic strategy for enhancing PARPi treatment outcomes in OC patients.

Automatic quantification of tumor-stroma ratio as a prognostic marker for pancreatic cancer.

This study aims to introduce an innovative multi-step pipeline for automatic tumor-stroma ratio (TSR) quantification as a potential prognostic marker for pancreatic cancer, addressing the limitations of existing staging systems and the lack of commonly used prognostic biomarkers. The proposed approach involves a deep-learning-based method for the automatic segmentation of tumor epithelial cells, tumor bulk, and stroma from whole-slide images (WSIs). Models were trained using five-fold cross-validation and evaluated on an independent external test set. TSR was computed based on the segmented components. Additionally, TSR's predictive value for six-month survival on the independent external dataset was assessed. Median Dice (inter-quartile range (IQR)) of 0.751(0.15) and 0.726(0.25) for tumor epithelium segmentation on internal and external test sets, respectively. Median Dice of 0.76(0.11) and 0.863(0.17) for tumor bulk segmentation on internal and external test sets, respectively. TSR was evaluated as an independent prognostic marker, demonstrating a cross-validation AUC of 0.61±0.12 for predicting six-month survival on the external dataset. Our pipeline for automatic TSR quantification offers promising potential as a prognostic marker for pancreatic cancer. The results underscore the feasibility of computational biomarker discovery in enhancing patient outcome prediction, thus contributing to personalized patient management.

The role of preoperative FPR and FAR in prognostic evaluation of stages II and III radical colorectal cancer: A single-center retrospective study.

The inflammatory and nutritional states of body are 2 important causes associated with the initiation and progression of colorectal cancer (CRC). The aim of this study is to investigate the prognostic evaluation value of preoperative fibrinogen-to-prealbumin ratio (FPR) and preoperative fibrinogen-to-albumin ratio (FAR) in CRC. The clinical data of 350 stages II and III patients with CRC who received radical resection were retrospectively analyzed. All patients were followed up for 5 years to observe the overall survival and disease-free survival of 5 years and analyze the relationship between preoperative FPR and FAR and prognosis of all enrolled patients. In addition, we analyzed the diagnostic and application value of combined biomarkers. This study showed high-level preoperative FPR and FAR were significantly associated with poor overall survival and disease-free survival of stages II and III patients with CRC. The elevated preoperative FPR and FAR level was significantly related to age, tumor differentiation level, TNM stage, vascular infiltration, carcinoembryonic antigen, carbohydrate antigen199, etc. The combination of FPR, FAR, neutrophil-to-lymphocyte ratio, and carbohydrate antigen199 had the maximum area under curve (AUC = 0.856, 95% CI: 0.814-0.897, Sen = 78.20%, Spe = 82.49%, P < .05) under the receiver-operating characteristics curve. The preoperative FPR and FAR have important prognostic value and they can be used as independent prognostic marker for patients with stages II and III CRC undergoing radical resection. Moreover, the combination of biomarkers could further enhance the diagnostic and prognostic efficacy of CRC.

Serum IL-24 combined with CA125 as screening and prognostic biomarkers for NSCLC.

Noninvasive and effective methods for early screening of non-small cell lung cancer(NSCLC) still need to be developed. At present, a reasonable conclusion is that a combination of tumor markers is a superior predictor of screening. Cytokines, as important regulators of cancer development, have great potential for the screening and prognosis of NSCLC. This study screened novel biomarkers related to the early screening and prognosis of NSCLC. In the present study, the biological significance and immunoregulation of interleukin-24(IL-24) were analyzed based on The Cancer Genome Atlas data. Next, 150 serum samples from initially treated patients with NSCLC and 70 controls were collected, and we obtained pathological sections from 60 patients with NSCLC. The ELISA and immunohistochemistryresults showed the differential expression of IL-24 and carbohydrate antigen 125(CA125). The results show that IL-24 is an important tumor suppressor in NSCLCthat helps to improve the poor prognosis of these patients. A significantly negative correlation between IL-24 and CA125 levels was also found. Notably, serum IL-24 levels were significantly negatively correlated with the TNM stage of patients with NSCLC, consistent with an important role for tumor suppressors in NSCLC. The receiver operating characteristic curve analysis showed that a combination of IL-24 and CA125 was an effective panel for discriminating patients with NSCLC from HD, and individuals with other lung diseases. Serum IL-24 and CA125 levels were identified as independent prognostic markers for NSCLC. The IL-24 and CA125 panel exhibited good performance in the screening of NSCLC.

Can platelet distribution width lymphocyte ratio be a novel biomarker for predicting survival in metastatic renal cell cancer?

Renal cell carcinoma (RCC) constitutes 3% of all malignant tumors in the adult patient population (1). As in other cancer processes, inflammation affects each step of tumor formation, including initiation of tumorigenesis, tumor promotion, and metastatic progression in RCC (2,3). It is widely accepted that C-reactive protein, fibrinogen, neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio, and platelet-lymphocyte ratio (PLR) are markers of inflammation in both inflammatory diseases and malignant disease processes (2,3). Furthermore, a relatively high NLR was reported to be associated with an unfavorable prognosis and reduced overall survival in urological cancers (4,5). Platelets can secrete active metabolites and proteins and take a significant role in various processes such as inflammation, sepsis, and tissue regeneration (5). In addition, it is known that they can release growth factors, including platelet-derived growth factor (PDGF), transforming growth factor-beta, and vascular endothelial growth factor (VEGF), which may all induce tumor angiogenesis and growth (6). In line with these findings, Tsujino et al. reported that platelet count could be an independent prognostic marker of overall survival and recurrence-free survival for patients with localized RCC (7). Additionally, Wang et al. stated that a high PLR value indicated an unfavorable prognosis in all urological cancers (8). Although several studies investigated the significance of hematological indices such as NLR and PLR in localized or metastatic RCC (mRCC), none focused on the platelet distribution width-lymphocyte ratio (PDWLR) (7,9,10). Therefore, this study aimed to analyze the prognostic significance of these platelet parameters in patients with mRCC.

Lactylproteome analysis indicates histone H4K12 lactylation as a novel biomarker in triple-negative breast cancer.

The established link between posttranslational modifications of histone and non-histone lysine (K) residues in cell metabolism, and their role in cancer progression, is well-documented. However, the lactylation expression signature in triple-negative breast cancer (TNBC) remains underexplored. We conducted a comprehensive lactylproteome profiling of eight pairs of TNBC samples and their matched adjacent tissues. This was achieved through 4-Dimensional label-free quantitative proteomics combined with lactylation analysis (4D-LFQP-LA). The expression of identified lactylated proteins in TNBC was detected using immunoblotting and immunohistochemistry (IHC) with specific primary antibodies, and their clinicopathological and prognostic significance was evaluated. Our analysis identified 58 lactylation sites on 48 proteins, delineating the protein lactylation alteration signature in TNBC. Bioinformatic and functional analyses indicated that these lactylated proteins play crucial roles in regulating key biological processes in TNBC. Notably, lactylation of lysine at position 12 (H4K12lac) in the histone H4 domain was found to be upregulated in TNBC. Further investigations showed a high prevalence of H4K12lac upregulation in TNBC, with positive rates of 93.19% (137/147) and 92.93% (92/99) in TNBC tissue chip and validation cohorts, respectively. H4K12lac expression correlated positively with Ki-67 and inversely with overall survival (OS) in TNBC (HR [hazard ratio] =2.813, 95%CI [credibility interval]: 1.242-6.371, P=0.0164), suggesting its potential as an independent prognostic marker (HR=3.477, 95%CI: 1.324-9.130, P=0.011). Lactylation is a significant post-translational modification in TNBC proteins. H4K12lac emerges as a promising biomarker for TNBC, offering insights into the lactylation profiles of TNBC proteins and linking histone modifications to clinical implications in TNBC.

Challenges in the Assessment of Medullary Bone Invasion in Oral Cavity Cancers and Its Prognostic Significance.

As per AJCC 8th edition TNM staging system, bone invasion is a poor prognostic marker that upstages oral cavity squamous carcinoma (OSCC) to pT4a. Cortical erosion alone of bone or tooth socket by a gingival primary is not sufficient to upstage a tumour. The differentiation of cortical erosion from invasion through the cortical bone into the medulla is often challenging, limiting accurate staging. This review aims to assess the difficulties in differentiating cortical erosion from medullary invasion and evaluate the prognostic significance of different patterns of bone involvement. A retrospective review of OSCC with primary curative surgery and bone resection treated at a single-center over 10years, was performed to assess the prognostic significance of bone invasion. Hematoxylin-eosin stained slides of a subset of cases were re-reviewed in a planned manner to assess difficulties in precise categorization (no invasion/erosion/cortical invasion and medullary invasion), evaluate interobserver agreement, and correlate with clinical outcome. Five hundred and ninety patients were included, with a median follow-up of 28months. On univariate analysis, the 3-year local, nodal and distant metastasis control were not significantly different in the 3 groups of no invasion, erosion, and invasion (p = 0.43, 0.47, and 0.47, respectively). Overall survival (OS) at 3years was 78.1% and disease-free-survival(DFS) was 63.7% in the entire cohort. On univariate analysis, there was significant difference in OS and DFS based on these groups. This did not translate into independent prognostic benefit on multivariable analysis (p = 0.75 and 0.19, respectively). The independent prognostic factors were margin positivity, tumor differentiation, perineural invasion and pathological nodal involvement. Planned re-review of a subset of 202 cases resulted in a change in bone involvement category in 26/202 cases, which was mainly due to difficulty in assessing cortico-medullary junction near the tooth socket and bone fragmentation. The assessment showed moderate to near complete agreement (kappa 0.59-0.82) between 2 observers. Our study shows that bone involvement is not an independent prognostic marker and there is no specific correlation of medullary invasion with outcome over those that showed cortical erosion. Several factors contribute to difficulties and interobserver variability in assessing bone involvement.

Abstract PO3-14-04: Prognostic value of systemic inflammatory markers in neoadjuvant chemotherapy for breast triple negative cancer with pembrolizumab: development of a nomogram

Abstract Introduction: Systemic inflammatory markers derived from peripheral blood cells, such as the neutrophil-lymphocyte ratio (NLR), derived neutrophil-lymphocyte ratio (dNLR), platelet-lymphocyte ratio (PLR), and lymphocyte-monocyte ratio (LMR), have shown promise as prognostic markers for various cancer types. Inflammation plays a crucial role in cancer development, progression, metastasis, and resistance to treatment. However, only a few preoperative biomarkers have been identified as independent prognostic markers. Systemic inflammatory markers offer a reliable and easily accessible approach for prognosis evaluation. Materials and Methods: This study evaluated two groups of patients who received neoadjuvant chemotherapy for triple-negative breast cancer outside of clinical trials. The first group underwent neoadjuvant chemotherapy in 2021 with the EC X4 and weekly paclitaxel regimen, whereas the second group received neoadjuvant chemotherapy in 2022 following the KEYNOTE-522 study protocol with pembrolizumab. A total of 44 patients were included, with 23 patients in the pembrolizumab group. The NLR was defined as the absolute blood neutrophil count divided by the absolute lymphocyte count, and the derived neutrophil/lymphocyte ratio (dNLR) was defined as the absolute neutrophil count divided by the derived lymphocyte count (absolute leukocyte count —neutrophil count). The PLR was defined as the absolute platelet count divided by the absolute lymphocyte count. The LMR was defined as the absolute lymphocyte count divided by the absolute monocyte count. The association between systemic inflammatory markers (NLR, dNLR, PLR, and LMR) and pathological complete response (pCR) was analyzed using statistical tests. Inflammatory markers were evaluated at the time of diagnosis, at the time of chemotherapy regimen change, and two weeks before surgery. The χ2 test or Fisher’s exact test was used to analyze the correlation between the inflammatory indices and clinicopathologic parameters. Student’s t-test was used to compare different groups of continuous parametric data. Results: The pCR rates were 67% in the standard therapy group and 87% in the pembrolizumab group. There were no significant differences in other clinical characteristics between the two groups. The NLR, dNLR, PLR, and LMR at 6 months showed statistically significant differences compared to baseline levels. This difference was more evident in patients undergoing pembrolizumab therapy. ROC curves for the pembrolizumab group demonstrated an area under the curve (AUC) of 0.737, indicating a strong correlation between these systemic inflammatory markers and pCR. Based on these data, a nomogram was constructed to predict the likelihood of achieving pCR in patients undergoing neoadjuvant pembrolizumab therapy. Conclusion: This study highlights the potential of systemic inflammatory markers as prognostic indicators in patients with TNBC undergoing neoadjuvant chemotherapy. The significant differences observed in the pembrolizumab group and the high AUC of the ROC curves suggest the utility of these markers in predicting treatment response. The developed nomogram provides a practical tool for clinicians to estimate the probability of pCR based on NLR, dNLR, PLR, and LMR. Further research and validation are required to confirm the clinical utility of these markers in larger patient cohorts. Nomogram –insert figure image– ROC curve –insert figure image– Citation Format: Filippo Giovanardi, Giancarlo Bisagni, Elisa Gasparini, Alessandra Bologna, Roberto Di Cicilia, Gabriella Moretti, Claudia Degli Esposti, Carmine Pinto. Prognostic value of systemic inflammatory markers in neoadjuvant chemotherapy for breast triple negative cancer with pembrolizumab: development of a nomogram [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-14-04.

52: Sarcopenia as an independent prognostic marker in NSCLC patients with BMs treated with GKRS

52: Sarcopenia as an independent prognostic marker in NSCLC patients with BMs treated with GKRS

61: SII and NLR are independent prognostic markers of patients with NSCLC BM treated with GKRS

61: SII and NLR are independent prognostic markers of patients with NSCLC BM treated with GKRS

The Evolving Landscape of Flowcytometric Minimal Residual Disease Monitoring in B-Cell Precursor Acute Lymphoblastic Leukemia.

Detection of minimal residual disease (MRD) is a major independent prognostic marker in the clinical management of pediatric and adult B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL), and risk stratification nowadays heavily relies on MRD diagnostics. MRD can be detected using flow cytometry based on aberrant expression of markers (antigens) during malignant B-cell maturation. Recent advances highlight the significance of novel markers (e.g., CD58, CD81, CD304, CD73, CD66c, and CD123), improving MRD identification. Second and next-generation flow cytometry, such as the EuroFlow consortium's eight-color protocol, can achieve sensitivities down to 10-5 (comparable with the PCR-based method) if sufficient cells are acquired. The introduction of targeted therapies (especially those targeting CD19, such as blinatumomab or CAR-T19) introduces several challenges for flow cytometric MRD analysis, such as the occurrence of CD19-negative relapses. Therefore, innovative flow cytometry panels, including alternative B-cell markers (e.g., CD22 and CD24), have been designed. (Semi-)automated MRD assessment, employing machine learning algorithms and clustering tools, shows promise but does not yet allow robust and sensitive automated analysis of MRD. Future directions involve integrating artificial intelligence, further automation, and exploring multicolor spectral flow cytometry to standardize MRD assessment and enhance diagnostic and prognostic robustness of MRD diagnostics in BCP-ALL.

A novel defined programmed cell death related gene signature for predicting the prognosis of serous ovarian cancer.

This study aims to explore the contribution of differentially expressed programmed cell death genes (DEPCDGs) to the heterogeneity of serous ovarian cancer (SOC) through single-cell RNA sequencing (scRNA-seq) and assess their potential as predictors for clinical prognosis. SOC scRNA-seq data were extracted from the Gene Expression Omnibus database, and the principal component analysis was used for cell clustering. Bulk RNA-seq data were employed to analyze SOC-associated immune cell subsets key genes. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were utilized to calculate immune cell scores. Prognostic models and nomograms were developed through univariate and multivariate Cox analyses. Our analysis revealed that 48 DEPCDGs are significantly correlated with apoptotic signaling and oxidative stress pathways and identified seven key DEPCDGs (CASP3, GADD45B, GNA15, GZMB, IL1B, ISG20, and RHOB) through survival analysis. Furthermore, eight distinct cell subtypes were characterized using scRNA-seq. It was found that G protein subunit alpha 15 (GNA15) exhibited low expression across these subtypes and a strong association with immune cells. Based on the DEGs identified by the GNA15 high- and low-expression groups, a prognostic model comprising eight genes with significant prognostic value was constructed, effectively predicting patient overall survival. Additionally, a nomogram incorporating the RS signature, age, grade, and stage was developed and validated using two large SOC datasets. GNA15 emerged as an independent and excellent prognostic marker for SOC patients. This study provides valuable insights into the prognostic potential of DEPCDGs in SOC, presenting new avenues for personalized treatment strategies.

Naive and regulatory B-cell transcription patterns guide the increased risk of papillary thyroid carcinoma in obesity.

A growing number of studies suggest a positive association between obesity and the high incidence of papillary thyroid cancer (PTC), suggesting that the abnormal levels of adipokines associated with obesity may be a risk factor for these aggressive thyroid cancers, but the underlying regulatory mechanisms are not yet clear. We downloaded bulk RNA sequence data for subcutaneous adipose tissue (SAT) in obesity and healthy population and tumor tissues of PTC from GEO database. Through analysis of Differential Expression Genes (DEGs), Gene Set Variation Analysis (GSVA) and Weighted Correlation Network Analysis (WGCNA), we identified co-expressed genes between obesity and PTC, and their pathways were mainly enriched in the regulation of B-cells. Furthermore, through TCGA-THCA (thyroid carcinoma) cohorts analysis, we identified B-cell regulatory-related genes LEF1, TNFRSF13C, SHLD2 and SHLD3 as independent prognostic markers of PTC. Next, we explored the transcriptional regulation mechanism of the increased risk of PTC in obesity through analysis of DNA methylation CpGs data and single-cell RNA sequences (scRNA-seq) from GEO database. PTC-induced hypomethylation of the promoter region may be involved in the transcriptional regulation of these genes, while these genes were further identified in naive and regulatory B-cells of both diseases. Notably, both of the gene expressions in naive and regulatory B-cells showed high similarity in both diseases. Our data reveals the high frequency of PTC in obese populations may be explained by the comparable transcriptional patterns of naive and regulatory B-cells, and offers novel insights for the analysis of critical genes and underlying biological mechanisms for obesity and PTC.

Stratification and prognostic evaluation of breast cancer subtypes defined by obesity-associated genes

ObjectiveBreast cancer was the most common type of cancer among women worldwide, significantly impacting their quality of life and survival rates. And obesity has been widely accepted as an important risk factor for breast cancer. However, the specific mechanisms by which obesity affects breast cancer were still unclear. Therefore, studying the impact mechanisms of obesity as a risk factor for breast cancer was of utmost importance.MethodsThis study was based on TCGA breast cancer RNA transcriptomic data and the GeneCard obesity gene set. Through single and multiple factor Cox analysis and LASSO coefficient screening, seven hub genes were identified. The independent mechanisms of these seven hub genes were evaluated from various aspects, including survival data, genetic mutation data, single-cell sequencing data, and immune cell data. Additionally, the risk prognosis model and the neural network diagnostic model were established to further investigate these seven hub genes. In order to achieve precision treatment for breast cancer (BRCA), based on the RNA transcriptomic data of the seven genes, 1226 BRCA patients were divided into two subtypes: BRCA subtype 1 and BRCA subtype 2. By studying and comparing the immune microenvironment, investigating the mechanisms of differential gene expression, and exploring the mechanisms of subnetworks, we aim to explore the clinical differences in the presentation of BRCA subtypes and achieve precision treatment for BRCA. Finally, qRT-PCR experiments were conducted to validate the conclusions of the bioinformatics analysis.ResultsThe 7 hub genes showed good diagnostic independence and can serve as excellent biomarkers for molecular diagnosis. However, they do not perform well as independent prognostic molecular markers for BRCA patients. When predicting the survival of BRCA patients, their AUC values at 1 year, 3 years, and 5 years are mostly below 0.5. Nevertheless, through the establishment of the risk prognosis model considering the combined effect of the seven hub genes, it was found that the survival prediction of BRCA patients can be significantly improved. The risk prognosis model, compared to the independent use of the seven hub genes as prognostic markers, achieved higher timeROC AUC values at 1 year, 3 years, and 5 years, with values of 0.651, 0.669, and 0.641 respectively. Additionally, the neural network diagnostic model constructed from the 7 genes performs well in diagnosing BRCA, with an AUC value of 0.94, accurately identifying BRCA patients. The two subtypes identified by the seven hub genes exhibited significant differences in survival period, with subtype 1 having a poor prognosis. The differential mechanisms between the two subtypes mainly originate from regulatory differences in the immune microenvironment. Finally, the results of this study’s bioinformatics analysis were validated through qRT-PCR experiments.Conclusion7 hub genes serve as excellent independent biomarkers for molecular diagnosis, and the neural network diagnostic model can accurately distinguish BRCA patients. In addition, based on the expression levels of these seven genes in BRCA patients, two subtypes can be reliably identified: BRCA subtype 1 and BRCA subtype 2, and these two subtypes showed significant differences in BRCA patient survival prognosis, proportion of immune cells, and expression levels of immune cells. Among them, patients with subtype 1 of BRCA had a poor prognosis.

Prognostic Utility of Left Atrial Strain From MRI Feature Tracking in Ischemic and Nonischemic Dilated Cardiomyopathy: A Multicenter Study.

BACKGROUND. MRI-based prognostic evaluation in patients with dilated cardiomyopathy (DCM) has historically used markers of late gadolinium enhancement (LGE) and feature tracking (FT)-derived left ventricular global longitudinal strain (LVGLS). Early data indicate that FT-derived left atrial strain (LAS) parameters, including reservoir, conduit, and booster, may also have prognostic roles in such patients. OBJECTIVE. The purpose of our study was to evaluate the prognostic utility of LAS parameters, derived from MRI FT, in patients with ischemic or nonischemic DCM, including in comparison with the traditional parameters of LGE and LVGLS. METHODS. This retrospective study included 811 patients with ischemic or nonischemic DCM (median age, 60 years; 640 men, 171 women) who underwent cardiac MRI at any of five centers. FT-derived LAS parameters and LVGLS were measured using two- and four-chamber cine images. LGE percentage was quantified. Patients were assessed for a composite outcome of all-cause mortality or heart failure hospitalization. Multivariable Cox regression analyses including demographic characteristics, cardiovascular risk factors, medications used, and a wide range of cardiac MRI parameters were performed. Kaplan-Meier analyses with log-rank tests were also performed. RESULTS. A total of 419 patients experienced the composite outcome. Patients who did, versus those who did not, experience the composite outcome had larger LVGLS (-6.7% vs -8.3%, respectively; p < .001) as well as a smaller LAS reservoir (13.3% vs 19.3%, p < .001), LAS conduit (4.7% vs 8.0%, p < .001), and LAS booster (8.1% vs 10.3%, p < .001) but no significant difference in LGE (10.1% vs 11.3%, p = .51). In multivariable Cox regression analyses, significant independent predictors of the composite outcome included LAS reservoir (HR = 0.96, p < .001) and LAS conduit (HR = 0.91, p < .001). LAS booster and LGE were not significant independent predictors in the models. LVGLS was a significant independent predictor only in a model that initially included LAS booster but not the other LAS parameters. In Kaplan-Meier analysis, all three LAS parameters were significantly associated with the composite outcome (p < .001). CONCLUSION. In this multicenter study, LAS reservoir and LAS conduit were significant independent prognostic markers in patients with ischemic or nonischemic DCM, showing greater prognostic utility than the currently applied markers of LVGLS and LGE. CLINICAL IMPACT. FT-derived LAS analysis provides incremental prognostic information in patients with DCM.

High LGALS3 expression induced by HCP5/hsa-miR-27b-3p correlates with poor prognosis and tumor immune infiltration in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is widely recognized for its unfavorable prognosis. Increasing evidence has revealed that LGALS3 has an essential function in initiating and developing several malignancies in humans. Nevertheless, thorough analysis of the expression profile, clinical prognosis, pathway prediction, and immune infiltration of LGALS3 has not been fully explored in HCC.MethodsIn this study, an initial pan-cancer analysis was conducted to investigate the expression and prognosis of LGALS3. Following a comprehensive analysis, which included expression analysis and correlation analysis, noncoding RNAs that contribute to the overexpression of LGALS3 were subsequently identified. This identification was further validated using HCC clinical tissue samples. TIMER2 and GEPIA2 were employed to examine the correlation between LGALS3 and HCP5 with immunological checkpoints, cell chemotaxis, and immune infiltration in HCC. The R program was applied to analyze the expression distribution of immune score in in HCC patients with high and low LGALS3 expression. The expression profiles of immune checkpoints were also analyzed. Use R to perform GSVA analysis in order to explore potential signaling pathways.ResultsFirst, we conducted pan-cancer analysis for LGALS3 expression level through an in-depth analysis of public databases and found that HCC has a high LGALS3 gene and protein expression level, which were then verified in clinical HCC specimens. Meanwhile, high LGALS3 gene expression is related to malignant progression and poor prognosis of HCC. Univariate and multivariate analyses confirmed that LGALS3 could serve as an independent prognostic marker for HCC. Next, by combining comprehensive analysis and validation on HCC clinical tissue samples, we hypothesize that the HCP5/hsa-miR-27b-3p axis could serve as the most promising LGALS3 regulation mechanism in HCC. KEGG and GO analyses highlighted that the LGALS3-related genes were involved in tumor immunity. Furthermore, we detected a significant positive association between LGALS3 and HCP5 with immunological checkpoints, cell chemotaxis, and immune infiltration. In addition, high LGALS3 expression groups had significantly higher immune cell scores and immune checkpoint expression levels. Finally, GSVA analysis was performed to predict potential signaling pathways linked to LGALS3 and HCP5 in immune evasion and metabolic reprogramming of HCC.ConclusionsOur findings indicated that the upregulation of LGALS3 via the HCP5/hsa-miR-27b-3p axis is associated with unfavorable prognosis and increased tumor immune infiltration in HCC.

Spatial distribution of tumor-resident macrophages as predictive biomarkers in endometrial cancer.

To investigate the role of CD47 expression and its relationship with tumor-resident macrophages, specifically at the tumor margin, in patients with type II endometrial cancer. This study aims to elucidate whether CD47 could serve as a prognostic marker and to understand the dynamics between CD47 and macrophages, which could inform new therapeutic strategies. A retrospective cohort study was conducted involving 75 patients of type II endometrial. Immunohistochemical analysis was performed to assess CD47 expression and macrophage markers (CD68 and CD163). The study found no direct correlation between CD47 expression levels and overall survival (p = 0.32), challenging its role as an independent prognostic marker in type II endometrial cancer. The higher expression of CD47 had significantly less incidence of endometrioid carcinoma G3 (p = 0.047). The negative correlation between CD47 H-score and the density of CD68-positive macrophages at tumor margin was statistically significant (p = 0.049). A high density of CD68-positive macrophages at the tumor margin but a low density of CD163-positive macrophages at the tumor margin were associated with poorer prognosis (p = 0.036). The complex interaction between CD47 and macrophages, particularly at the tumor margin, suggests new avenues for targeted therapy in type II endometrial cancer.

Subcellular expression of MTA1, HIF1A and p53 in primary tumor predicts aggressive triple negative breast cancers: a meta-analysis based study.

The prevalence of TNBC in India is higher compared to western countries. There is a multitude of biomarkers associated with different clinical outcomes of TNBC with contradictory reports. Identification of a set of specific biomarkers from the very many number of proteins reported in the literature to predict prognosis of TNBC is an urgent clinical need. A systematic review of key molecular biomarkers in cohort studies that have been investigated for their role in breast cancer prognosis was conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was followed. A meta-analysis was used to evaluate their pooled hazard ratio (HR) and the corresponding 95% confidence interval (95% CI) statistically. Immunohistochemical characterization of the meta-analyzed markers were performed in a cohort of 200 retrospective TNBC and 100 non TNBC patient tissues. Kaplan-Meier plot were used to evaluate disease free survival (DFS), and overall survival (OS). Cox regression models were used to evaluate predictors of DFS and OS. Using a meta-analytical approach, we consolidated the biomarker signatures associated with survival outcomes in breast cancers. The promising markers that emerged for the prediction of DFS and OS included E-Cadherin, Survivin, p53, MTA1, HIF1A, CD133, Vimentin and CK5/6. Evaluation of these markers in tumor tissue revealed that subcellular localization of p53, MTA1 and HIF1A had a significant association in predicting TNBC prognosis. Kaplan Meier plot revealed that p53 (OS p = 0.007, DFS p = 0.004), HIF 1A (OS p = 0.054, DFS p = 0.009) and MTA1 (OS p = 0.043, DFS = p = 0.001) expression in the primary tumor tissue were found to be significantly correlated with poor OS and DFS, whereas expression of Survivin (DFS p = 0.024) and E Cadherin (DFS p = 0.027) correlated with DFS alone in TNBC. Univariate analysis revealed that p53, HIF1A and MTA1 could be independent prognostic markers. Our study suggests cytoplasmic over expression of HIF1A, nuclear over expression of MTA1 and mutated p53 in the primary tumor tissue of TNBC have significance as markers predicting survival of TNBC patients.

SLC7A11 inhibits ferroptosis and downregulates PD-L1 levels in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a prevalent form of lung cancer originating from lung glandular cells with low survival rates despite recent therapeutic advances due to its diverse and complex nature. Recent evidence suggests a link between ferroptosis and the effectiveness of anti-PD-L1 therapy, with potential synergistic effects. Our study comprehensively analyzed the expression patterns of ferroptosis regulators in LUAD and their association with prognosis and PD-L1 expression. Furthermore, we identified two distinct subtypes of LUAD through consensus clustering of ferroptosis regulators, revealing significant tumor heterogeneity, divergent PD-L1 expression, and varying prognoses between the subtypes. Among the selected ferroptosis regulators, SLC7A11 emerged as an independent prognostic marker for LUAD patients and exhibited a negative correlation with PD-L1 expression. Subsequent investigations revealed high expression of SLC7A11 in the LUAD population. In vitro experiments demonstrated that overexpression of SLC7A11 led to reduced PD-L1 expression and inhibited ferroptosis in A549 cells, underscoring the significant role of SLC7A11 in LUAD. Additionally, pan-cancer analyses indicated an association between SLC7A11 and the expression of immune checkpoint genes across multiple cancer types with poor prognoses. From a clinical standpoint, these findings offer a foundation for identifying and optimizing potential combination strategies to enhance the therapeutic effectiveness of immune checkpoint inhibitors and improve the prognosis of patients with LUAD.

Abstract LB274: Nuclear transporter HIKESHI is a novel independent poor overall survival for pancreatic cancer; targeting can inhibit pancreatic cancer growth via HSP70 suppression

Abstract HIKESHI, under heat stress conditions, has been reported to transport molecular chaperone HSP70 into the nucleus to prevent cancer cell death from heat stress. The tumor-supporting roles of molecular chaperones in various solid tumors are explored extensively. Yet, the sole targeting of the molecular chaperones could not significantly impact anticancer treatment. Thus, we hypothesized that the specific transporter protein HIKESHI might improve this outcome. However, understanding of the clinical relevance of HIKESHI in pancreatic cancer remained unclear, and few studies addressed the HIKESHI role in cancer and whether targeting can inhibit pancreatic cancer cell viability and the other HSPs. Here, we first investigated the expression pattern of the HIKESHI protein in surgically resected pancreatic cancer samples (n=142) and analyzed the clinical relevance of the HIKESHI. We found that the HIKESHI protein was overexpressed in cancer compared to the adjacent normal tissue, and positive expression of cancer HIKESHI was related to poor overall survival. In addition, HIKESHI-positive expression in cancer was identified as an independent prognostic marker for overall survival. Next, using shRNA, we established the stable HIKESHI-suppressed pancreatic cancer cell line (PANC-1). HIKESHI suppression inhibited cell growth and colony formation ability in vitro. The expression and nuclear translocation of HSP70 and HSP110/105 were suppressed in HIKESHI-suppressed cells compared to the control shRNA cells despite no heat stress conditions. Furthermore, we found that the tumor growth, HIKESHI, and Ki67 expression in HIKESHI-suppressed tumors were inhibited compared to the control shRNA tumors. Next, we performed Cap Analysis of Gene Expression and IP-MS analysis to discover the potential downstream and novel interactive partner of the HIKESHI protein. The extensive mechanism of these analyses is under investigation. Our findings suggest that targeting HIKESHI may be a promising therapeutic strategy against refractory pancreatic cancer. Citation Format: Bilguun Erkhem-Ochir, Takehiko Yokobori, Gendensuren Dorjkhorloo, Haruka Okami, Takaomi Seki, Norifumi Harimoto, Ryo Muranushi, Kouki Hoshino, Kei Hagiwara, Norihiro Ishii, Mariko Tsukagoshi, Kenichiro Araki, Hiroshi Saeki, Ken Shirabe. Nuclear transporter HIKESHI is a novel independent poor overall survival for pancreatic cancer; targeting can inhibit pancreatic cancer growth via HSP70 suppression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB274.