Prognostic Value For Overall Survival Research Articles

Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study.

To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment. We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively. In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively). Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients.

Comparison of discovery rates and prognostic utility of [68Ga]Ga-PSMA-11 PET/CT and circulating tumor DNA in prostate cancer—a cross-sectional study

BackgroundCirculating-tumor DNA (ctDNA) and prostate-specific membrane antigen (PSMA) ligand positron-emission tomography (PET) enable minimal-invasive prostate cancer (PCa) detection and survival prognostication. The present study aims to compare their tumor discovery abilities and prognostic values.MethodsOne hundred thirty men with confirmed PCa (70.5 ± 8.0 years) who underwent [68Ga]Ga-PSMA-11 PET/CT (184.8 ± 19.7 MBq) imaging and plasma sample collection (March 2019–August 2021) were included. Plasma-extracted cell-free DNA was subjected to whole-genome-based ctDNA analysis. PSMA-positive tumor lesions were delineated and their quantitative parameters extracted. ctDNA and PSMA PET/CT discovery rates were compared, and the prognostic value for overall survival (OS) was evaluated.ResultsPSMA PET discovery rates according to castration status and PSA ranges did differ significantly (P = 0.013, P < 0.001), while ctDNA discovery rates did not (P = 0.311, P = 0.123). ctDNA discovery rates differed between localized and metastatic disease (P = 0.013). Correlations between ctDNA concentrations and PSMA-positive tumor volume (PSMA-TV) were significant in all (r = 0.42, P < 0.001) and castration-resistant (r = 0.65, P < 0.001), however not in hormone-sensitive patients (r = 0.15, P = 0.249). PSMA-TV and ctDNA levels were associated with survival outcomes in the Logrank (P < 0.0001, P < 0.0001) and multivariate Cox regression analysis (P = 0.0023, P < 0.0001).ConclusionThese findings suggest that PSMA PET imaging outperforms ctDNA analysis in detecting prostate cancer across the whole spectrum of disease, while both modalities are independently highly prognostic for survival outcomes.Graphical

CD200 is overexpressed in the pancreatic tumor microenvironment and predictive of overall survival

Pancreatic cancer is an aggressive disease with a 5 year survival rate of 13%. This poor survival is attributed, in part, to limited and ineffective treatments for patients with metastatic disease, highlighting a need to identify molecular drivers of pancreatic cancer to target for more effective treatment. CD200 is a glycoprotein that interacts with the receptor CD200R and elicits an immunosuppressive response. Overexpression of CD200 has been associated with differential outcomes, depending on the tumor type. In the context of pancreatic cancer, we have previously reported that CD200 is expressed in the pancreatic tumor microenvironment (TME), and that targeting CD200 in murine tumor models reduces tumor burden. We hypothesized that CD200 is overexpressed on tumor and stromal populations in the pancreatic TME and that circulating levels of soluble CD200 (sCD200) have prognostic value for overall survival. We discovered that CD200 was overexpressed on immune, stromal, and tumor populations in the pancreatic TME. Particularly, single-cell RNA-sequencing indicated that CD200 was upregulated on inflammatory cancer-associated fibroblasts. Cytometry by time of flight analysis of PBMCs indicated that CD200 was overexpressed on innate immune populations, including monocytes, dendritic cells, and monocytic myeloid-derived suppressor cells. High sCD200 levels in plasma correlated with significantly worse overall and progression-free survival. Additionally, sCD200 correlated with the ratio of circulating matrix metalloproteinase (MMP) 3: tissue inhibitor of metalloproteinase (TIMP) 3 and MMP11/TIMP3. This study highlights the importance of CD200 expression in pancreatic cancer and provides the rationale for designing novel therapeutic strategies that target this protein.

A three-gene expression score for predicting clinical benefit to anti-PD-1 blockade in advanced renal cell carcinoma.

In the advanced renal cell carcinoma (RCC) scenario, there are no consistent biomarkers to predict the clinical benefit patients derived from immune checkpoint blockade (ICB). Taking this into consideration, herein, we conducted a retrospective study in order to develop and validate a gene expression score for predicting clinical benefit to the anti-PD-1 antibody nivolumab in the context of patients diagnosed with advanced clear cell RCC enrolled in the CheckMate-009, CheckMate-010, and CheckMate-025 clinical trials. First, a three-gene expression score (3GES) with prognostic value for overall survival integrating HMGA1, NUP62, and ARHGAP42 transcripts was developed in a cohort of patients treated with nivolumab. Its prognostic value was then validated in the TCGA-KIRC cohort. Second, the predictive value for nivolumab was confirmed in a set of patients from the CheckMate-025 phase 3 clinical trial. Lastly, we explored the correlation of our 3GES with different clinical, molecular, and immune tumor characteristics. If the results of this study are definitively validated in other retrospective and large-scale, prospective studies, the 3GES will represent a valuable tool for guiding the design of ICB-based clinical trials in the aRCC scenario in the near future.

Identification of prognostic factors for survival in patients with metastatic gastric adenocarcinoma in a Mexican population

Introduction and aimsGastric adenocarcinoma is among the high-ranking tumors, with respect to frequency and mortality, worldwide. The inflammatory process and immune system activity are associated with oncologic control. Our aim was to identify whether the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and other variables are prognostic factors for survival in patients with metastatic gastric cancer in a Mexican population. Material and methodsPatients diagnosed with metastatic gastric adenocarcinoma, hospitalized within the time frame of December 2011 to 2021, were analyzed. The NLR, PLR, and albumin and hemoglobin levels obtained from blood samples were calculated. Functional status (ECOG and Karnofsky), sex, histology, and the presence of signet ring cells were also considered possible prognostic factors. Each factor’s prognostic value for overall survival was determined through univariate and multivariate analyses. ResultsThe study included 956 patients diagnosed with metastatic gastric cancer, of whom 494 (51.7%) were men and 462 (48.3%) were women. The main histologic finding was diffuse adenocarcinoma (n = 619, 64.7%), followed by intestinal adenocarcinoma (n = 293, 30.6%), and the presence of signet ring cells was found in 659 (68.9%) patients. Diagnostic laparoscopy was performed on 238 patients (24.9%) to confirm peritoneal carcinomatosis. The multivariate analysis showed that an NLR above 3.2 (HR 1.51, 95% CI 1.27-1.8; p < 0.001), albumin below 3.5 g/dl (HR 1.25, CI 1.06 - 1.47; p = 0.006), and an ECOG performance status of 2 or higher (HR 1.39, CI 1.10-1.76; p = 0.005) were independent factors that predicted a lower survival rate, whereas a Karnofsky score above 70% (HR 0.69, CI 0.53-0.91; p = 0.008) was associated with a better survival rate. Lastly, the PLR was not statistically significant in the multivariate analysis. ConclusionsThe NLR, nutritional status assessed through albumin measurement, and functional status can act as independent prognostic survival factors in hospitalized Mexican patients diagnosed with metastatic gastric adenocarcinoma and be taken into account during therapeutic decision-making.

Subtype-Specific Survival of Young Women with Breast Cancer and Its Interaction with the Germline BRCA Status.

Data are scarce on the role of pathogenic germline variants in BRCA1 and BRCA2 (gBRCAm) in subtype-specific survival in young women who develop breast cancer under the age of 40. This retrospective, real-world cohort study assessed the distant disease-free survival (DDFS) and overall survival (OS) of young women diagnosed with breast cancer between 2008 and 2019 while taking into consideration the interaction of clinical subtypes and the gBRCA status. Among 473 women, HR+/Her2- was the most common subtype (49.0%), followed by TNBC (31.3%), HR+/Her2+ (13.7%), and Her2+/HR- (5.9%). The gBRCA status was known for 319 cases (gBRCAwt (wild-type - without pathogenic variants in BRCA1 or BRCA2): 204, gBRCA1m: 83, gBRCA2m: 31, 1 patient with both). The distribution of clinical subtypes varied depending on the gBRCA status (p < 0.001). In survival analysis with a median follow-up of 43 months, the unadjusted DDFS and OS were worse for gBRCAwt TNBC compared to both HR+ subtypes, but not for gBRCAm TNBC patients. T-stage, nodal involvement, and the gBRCA status were identified as significant for survival in TNBC. In TNBC, gBRCAm was associated with better DDFS and OS than gBRCAwt (5-year DDFS 81.4% vs. 54.3%, p = 0.012 and 5-year OS 96.7% vs. 62.7%, p < 0.001). In contrast, in HR+/Her2- patients, gBRCAm patients showed a tendency for worse survival, though not statistically significant. Subtype-specific survival in young women with breast cancer needs to be evaluated in interaction with the gBRCA status. For TNBC, gBRCAm is of favorable prognostic value for overall survival, while patients with gBRCAwt TNBC need to be considered to have the highest risk for adverse survival outcomes.

Impact of presentation timing in metastatic hormone-sensitive prostate cancer: Characterization of patients and identification of prognostic factors.

The treatment and surveillance of metastatic hormone-sensitive prostate cancer (mHSPC) has evolved since the introduction of several treatment intensification options associated with hormonal blockade and classifications based on the timing of metastatic disease presentation and disease volume. Using a hospital-based registry, we aimed to assess whether these new classifications are applicable to our population, as few studies have demonstrated their prognostic value for overall survival (OS) and time to development of castration-resistant prostate cancer (CRPC), and to establish prognostic factors in our population. A retrospective cohort of mHSPC patients who were attended at an oncology referral hospital in Bogota between 2017 and 2021 were included in this study. The primary and secondary endpoints were OS and time to CRPC. The distribution of outcome measures was estimated using the Kaplan-Meier method. Proportional hazard models were constructed using the Cox regression approach and stratified according to risk factors. The study cohort included 373 patients. The median castration resistance-free survival was 48 months (CI: 32-73 months), and OS was 43 months (CI: 37-48 months). In multivariate analysis, nodal staging, ECOG status, and surgical castration were independent prognostic factors. In our hospital-based registry, the independent impact of the time of presentation on castration-resistant-free survival or OS could not be demonstrated, nor could the grouping of prognostic categories based on metastatic presentation temporality and volume. Other independent prognostic factors have been proposed.

MIHIC: a multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification.

Immunohistochemistry (IHC) is a widely used laboratory technique for cancer diagnosis, which selectively binds specific antibodies to target proteins in tissue samples and then makes the bound proteins visible through chemical staining. Deep learning approaches have the potential to be employed in quantifying tumor immune micro-environment (TIME) in digitized IHC histological slides. However, it lacks of publicly available IHC datasets explicitly collected for the in-depth TIME analysis. In this paper, a notable Multiplex IHC Histopathological Image Classification (MIHIC) dataset is created based on manual annotations by pathologists, which is publicly available for exploring deep learning models to quantify variables associated with the TIME in lung cancer. The MIHIC dataset comprises of totally 309,698 multiplex IHC stained histological image patches, encompassing seven distinct tissue types: Alveoli, Immune cells, Necrosis, Stroma, Tumor, Other and Background. By using the MIHIC dataset, we conduct a series of experiments that utilize both convolutional neural networks (CNNs) and transformer models to benchmark IHC stained histological image classifications. We finally quantify lung cancer immune microenvironment variables by using the top-performing model on tissue microarray (TMA) cores, which are subsequently used to predict patients' survival outcomes. Experiments show that transformer models tend to provide slightly better performances than CNN models in histological image classifications, although both types of models provide the highest accuracy of 0.811 on the testing dataset in MIHIC. The automatically quantified TIME variables, which reflect proportions of immune cells over stroma and tumor over tissue core, show prognostic value for overall survival of lung cancer patients. To the best of our knowledge, MIHIC is the first publicly available lung cancer IHC histopathological dataset that includes images with 12 different IHC stains, meticulously annotated by multiple pathologists across 7 distinct categories. This dataset holds significant potential for researchers to explore novel techniques for quantifying the TIME and advancing our understanding of the interactions between the immune system and tumors.

Comprehensive analysis the prognostic and immune characteristics of mitochondrial transport-related gene SFXN1 in lung adenocarcinoma

BackgroundMitochondria, which serve as the fundamental organelle for cellular energy and metabolism, are closely linked to the growth and survival of cancer cells. This study aims to identify and assess Sideroflexin1 (SFXN1), an unprecedented mitochondrial gene, as a potential prognostic biomarker for lung adenocarcinoma (LUAD).MethodsThe mRNA and protein levels of SFXN1 were investigated based on the Cancer Genome Atlas (TCGA) LUAD dataset, and then validated by real-time quantitative PCR, Western Blotting and immunohistochemistry from our clinical samples. The clinical correlation and prognostic value were evaluated by the TCGA cohort and verified via our clinical dataset (n = 90). The somatic mutation, drug sensitivity data, immune cell infiltration and single-cell RNA sequencing data of SFXN1 were analyzed through public databases.ResultsSFXN1 was markedly upregulated at both mRNA and protein levels in LUAD, and high expression of SFXN1 were correlated with larger tumor size, positive lymph node metastasis, and advanced clinical stage. Furthermore, SFXN1 upregulation was significantly associated with poor clinical prognosis. SFXN1 co-expressed genes were also analyzed, which were mainly involved in the cell cycle, central carbon metabolism, DNA repair, and the HIF-1α signaling pathway. Additionally, SFXN1 expression correlated with the expression of multiple immunomodulators, which act to regulate the tumor immune microenvironment. Results also demonstrated an association between SFXN1 expression and increased immune cell infiltration, such as activated CD8 + T cells, natural killer cells (NKs), activated dendritic cells (DCs), and macrophages. LUAD patients with high SFXN1 expression exhibited heightened sensitivity to multiple chemotherapies and targeted drugs and predicted a poor response to immunotherapy. SFXN1 represented an independent prognostic marker for LUAD patients with an improved prognostic value for overall survival when combined with clinical stage information.ConclusionsSFXN1 is frequently upregulated in LUAD and has a significant impact on the tumor immune environment. Our study uncovers the potential of SFXN1 as a prognostic biomarker and as a novel target for intervention in LUAD.

Identificación de factores pronósticos para supervivencia en pacientes con adenocarcinoma gástrico metastásico en la población mexicana

Introduction and aimsGastric adenocarcinoma is among the high-ranking tumors, with respect to frequency and mortality, worldwide. The inflammatory process and immune system activity are associated with oncologic control. Our aim was to identify whether the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), and other variables are prognostic factors for survival in patients with metastatic gastric cancer in a Mexican population. Material and methodsPatients diagnosed with metastatic gastric adenocarcinoma, hospitalized within the time frame of December 2011 to 2021, were analyzed. The NLR, PLR, and albumin and hemoglobin levels obtained from blood samples were calculated. Functional status (ECOG and Karnofsky), sex, histology, and the presence of signet ring cells were also considered possible prognostic factors. Each factor's prognostic value for overall survival was determined through univariate and multivariate analyses. ResultsThe study included 956 patients diagnosed with metastatic gastric cancer, of whom 494 (51.7%) were men and 462 (48.3%) were women. The main histologic finding was diffuse adenocarcinoma (n=619, 64.7%), followed by intestinal adenocarcinoma (n=293, 30.6%), and the presence of signet ring cells was found in 659 (68.9%) patients. Diagnostic laparoscopy was performed on 238 patients (24.9%) to confirm peritoneal carcinomatosis. The multivariate analysis showed that an NLR above 3.2 (HR 1.51, 95% CI 1.27-1.8; p<0.001), albumin below 3.5g/dl (HR 1.25, 95% CI 1.06-1.47; p=0.006), and an ECOG performance status of 2 or higher (HR 1.39, 95% CI 1.10-1.76; p=0.005) were independent factors that predicted a lower survival rate, whereas a Karnofsky score above 70% (HR 0.69, 95% CI 0.53-0.91; p=0.008) was associated with a better survival rate. Lastly, the PLR was not statistically significant in the multivariate analysis. ConclusionsThe NLR, nutritional status assessed through albumin measurement, and functional status can act as independent prognostic survival factors in hospitalized Mexican patients diagnosed with metastatic gastric adenocarcinoma, and be taken into account during therapeutic decision-making.

Frailty assessment by two screening instruments in non-elderly patients with head and neck cancer

PurposeFrailty assessment is often overlooked in non-elderly patients with cancer, possibly due to the lack of an effective frailty screening tool. This study aimed to evaluate the performance of two modern frailty screening tools, the Flemish version of the Triage Risk Screening Tool (fTRST) and the modified 5-Item Frailty Index (mFI-5), compared to the gold standard comprehensive geriatric assessment (GA) among non-elderly patients with head and neck cancer (HNC). MethodsWe prospectively included 354 consecutive patients aged < 65 years with newly diagnosed HNC scheduled for definitive concurrent chemoradiotherapy (CCRT) at three academic hospitals in Taiwan between January 2020 and December 2022. Frailty assessment using the GA, fTRST, and mFI-5 was performed in all patients to evaluate the relationship between frailty and treatment outcomes. ResultsThe prevalence of frailty was 27.1%, 37.0%, and 42.4% based on GA, mFI-5, and fTRST, respectively. mFI-5 and fTRST demonstrated good predictive value in identifying frail patients compared to the GA. Patients with frailty, as defined by GA, mFI-5, and fTRST, exhibited higher risks of treatment-related complications, incomplete treatment, and poorer baseline quality of life (QoL). However, only GA showed significant prognostic value for overall survival. ConclusionsFrailty assessment using fTRST and mFI-5 is valuable for predicting treatment-related adverse events, treatment tolerance, and QoL in non-elderly patients with HNC. Incorporating frailty assessment into the management of non-elderly cancer patients can aid in the identification of high-risk individuals. However, the performance of these tools varies, highlighting the need for further validation and refinement.

A tumor-infiltrating immune cells-related pseudogenes signature based on machine-learning predicts outcomes and immunotherapy responses in ovarian cancer

Previous researches have provided evidence for the significant involvement of pseudogenes in immune-related functions across different types of cancer. However, the mechanisms by which pseudogenes regulate immunity in ovarian cancer (OV) and their potential impact on clinical outcomes remain unclear. To address this gap in knowledge, our study utilized a novel computational framework to analyze a total of 491 samples from three public datasets. We employed a combination of 10 machine-learning algorithms to construct a signature known as the tumor-infiltrating immune cells-related pseudogenes signature (TIICPS). The TIICPS, consisting of 12 pseudogenes, demonstrated independent prognostic value for overall survival, surpassing conventional clinical traits, 62 published signatures, and TP53 and BRCA mutation status in three cohorts. Patients with low TIICPS exhibited heightened immune-related pathways, intricate genomic alterations, substantial immune infiltration, and greater potential for immunotherapy efficacy. Consequently, TIICPS holds promise as a predictive tool for prognosis and immunotherapy response in ovarian cancer.

Trends in Systemic Inflammatory Reaction (SIR) during Paclitaxel and Carboplatin Chemotherapy in Women Suffering from Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) is the most fatal gynaecological malignancy treated with cytoreductive surgery followed by adjuvant taxane-platinum-based chemotherapy. It has been shown that the pretreatment systemic inflammatory reaction (SIR) in women with OC can be evaluated using the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR) and systemic inflammatory index (SII), depending on the stage of disease, and has prognostic value for overall survival. The aim of this study was to evaluate the changes in NLR, LMR, PLR and SII during chemotherapy. A total of 107 women with EOC (23 with type I and 84 with type II tumours) were included in a retrospective single-centre analysis. The Kologomorov-Smirnoff, Kruskal-Wallis or Friedman analysis of variance tests were used for data analysis, and a p value of 0.05 was considered statistically significant. A significant decrease in NLR, PLR and SII but not LMR was observed during adjuvant treatment. Pretreatment NLR, PLR and SII were dependent on disease stage and tumour grade; however, this association was lost during therapy. Additionally, strong and positive mutual correlations between NLR, LMR, PLR and SII were sustained during the whole course of chemotherapy. During first-line adjuvant chemotherapy in women with EOC, a decrease in SIR is confirmed.

A new prognostic model including immune biomarkers, genomic proliferation tumor markers (AURKA and MYBL2) and clinical-pathological features optimizes prognosis in neoadjuvant breast cancer patients.

Up to 30% of breast cancer (BC) patients treated with neoadjuvant chemotherapy (NCT) will relapse. Our objective was to analyze the predictive capacity of several markers associated with immune response and cell proliferation combined with clinical parameters. This was a single-center, retrospective cohort study of BC patients treated with NCT (2001-2010), in whom pretreatment biomarkers were analyzed: neutrophil-to-lymphocyte ratio (NLR) in peripheral blood, CD3+ tumor-infiltrating lymphocytes (TILs), and gene expression of AURKA, MYBL2 and MKI67 using qRT-PCR. A total of 121 patients were included. Median followup was 12 years. In a univariate analysis, NLR, TILs, AURKA, and MYBL2 showed prognostic value for overall survival. In multivariate analyses, including hormone receptor, HER2 status, and response to NCT, NLR (HR 1.23, 95% CI 1.01-1.75), TILs (HR 0.84, 95% CI 0.73-0.93), AURKA (HR 1.05, 95% CI 1.00-1.11) and MYBL2 (HR 1.19, 95% CI 1.05-1.35) remained as independent predictor variables. Consecutive addition of these biomarkers to a regression model progressively increased its discriminatory capacity for survival. Should independent cohort studies validate these findings, management of early BC patients may well be changed.

Development of a necroptosis-related gene signature and the immune landscape in ovarian cancer

BackgroundNecroptosis is a novel type of programmed cell death distinct from apoptosis. However, the role of necroptosis in ovarian cancer (OC) remains unclear. The present study investigated the prognostic value of necroptosis-related genes (NRGs) and the immune landscape in OC.MethodsThe gene expression profiling and clinical information were downloaded from the TCGA and GTEx databases. Differentially expressed NRGs (DE-NRGs) between OC and normal tissueswere identified. The regression analyses were conducted to screen the prognostic NRGs and construct the predictive risk model. Patients were then divided into high- and low-risk groups, and the GO and KEGG analyses were performed to explore bioinformatics functions between the two groups. Subsequently, the risk level and immune status correlations were assessed through the ESTIMATE and CIBERSORT algorithms. The tumor mutation burden (TMB) and the drug sensitivity were also analyzed based on the two-NRG signature in OC.ResultsTotally 42 DE-NRGs were identified in OC. The regression analyses screened out two NRGs (MAPK10 and STAT4) with prognostic values for overall survival. The ROC curve showed a better predictive ability in five-year OS using the risk score. Immune-related functions were significantly enriched in the high- and low-risk group. Macrophages M1, T cells CD4 memory activated, T cells CD8, and T cells regulatory infiltration immune cells were associated with the low-risk score. The lower tumor microenvironment score was demonstrated in the high-risk group. Patients with lower TMB in the low-risk group showed a better prognosis, and a lower TIDE score suggested a better immune checkpoint inhibitor response in the high-risk group. Besides, cisplatin and paclitaxel were found to be more sensitive in the low-risk group.ConclusionsMAPK10 and STAT4 can be important prognosis factors in OC, and the two-gene signature performs well in predicting survival outcomes. Our study provided novel ways of OC prognosis estimation and potential treatment strategy.

Systematic Analysis of the Prognostic Significance and Roles of the Integrin Alpha Family in Non-Small Cell Lung Cancers.

Lung cancer is one of the most common cancer malignancies and the principal cause of cancer-associated deaths worldwide. Non-small cell lung cancers (NSCLCs) account for more than 80% of all lung cancer cases. Recent studies showed that the genes of the integrin alpha (α) (ITGA) subfamily play a fundamental role in various cancers. However, little is known about the expression and roles of distinct ITGA proteins in NSCLCs. Gene Expression Profiling Interactive Analysis and UALCAN (University of ALabama at Birmingham CANcer) web resources and The Cancer Genome Atlas (TCGA), ONCOMINE, cBioPortal, GeneMANIA, and Tumor Immune Estimation Resource databases were used to evaluate differential expression, correlations between the expression levels of individual genes, the prognostic value of overall survival (OS) and stage, genetic alterations, protein-protein interactions, and the immune cell infiltration of ITGAs in NSCLCs. We used R (v.4.0.3) software to conduct gene correlation, gene enrichment, and clinical correlation of RNA sequencing data of 1016 NSCLCs from TCGA. To evaluate the expression of ITGA5/8/9/L at the expression and protein levels, qRT-PCR, immunohistochemistry (IHC), and hematoxylin and eosin (H&E) were performed, respectively. Upregulated levels of ITGA11 messenger RNA and downregulated levels of ITGA1/3/5/7/8/9/L/M/X were observed in the NSCLC tissues. Lower expression of ITGA5/6/8/9/10/D/L was discovered to be expressively associated with advanced tumor stage or poor patient prognosis in patients with NSCLC. A high mutation rate (44%) of the ITGA family was observed in the NSCLCs. Gene Ontology functional enrichment analyses results revealed that the differentially expressed ITGAs could be involved in roles related to extracellular matrix (ECM) organization, collagen-containing ECM cellular components, and ECM structural constituent molecular functions. The results of the Kyoto Encyclopedia of Genes and Genomes analysis revealed that ITGAs may be involved in focal adhesion, ECM-receptor interaction, and amoebiasis; the expression of ITGAs was significantly correlated with the infiltration of diverse immune cells in NSCLCs. ITGA5/8/9/L was also highly correlated with PD-L1 expression. The validation results for marker gene expression in NSCLC tissues by qRT-PCR, IHC, and H&E staining indicated that the expression of ITGA5/8/9/L decreased compared with that in normal tissues. As potential prognostic biomarkers in NSCLCs, ITGA5/8/9/L may fulfill important roles in regulating tumor progression and immune cell infiltration.

High expression of TARS is associated with poor prognosis of endometrial cancer.

Endometrial cancer is the second largest and most common cancer in the world. It is urgent to explore novel biomarkers. Data were obtained from The Cancer Genome Atlas (TCGA) database. The receiver operating characteristic (ROC) curves, Kaplan-Meier curves and Cox analysis, nomograms, gene set enrichment analysis (GSEA) were conducted. Cell proliferation experiments were performed in Ishikawa cell. TARS was significantly highly expressed in serous type, G3 grade, and deceased status. Significant association was between high TARS expression with poor overall survival (P = 0.0012) and poor disease specific survival (P = 0.0034). Significant differences were observed in advanced stage, G3 and G4, and old. The stage, diabetes, histologic grade, and TARS expression showed independent prognostic value for overall survival of endometrial cancer. The stage, histologic grade, and TARS expression showed independent prognostic value for disease specific survival of endometrial cancer. Activated CD4+ T cell, effector memory CD4+ T cell, memory B cell and type 2 T helper cell may participate in the high TARS expression related immune response in endometrial cancer. The CCK-8 results showed significantly inhibited cell proliferation in si-TARS (P < 0.05) and promoted cell proliferation in O-TARS (P < 0.05), confirmed by the colony formation and live/dead staining. High TARS expression was found in endometrial cancer with prognostic and predictive value. This study will provide new biomarker TARS for diagnosis and prognosis of endometrial cancer.

Abstract P2-11-09: Association of 21-gene recurrence score with overall survival in phase 3 TAILORx trial

Abstract Background: The 21-gene recurrence score (RS) assay is a prognostic measurement originally established for distant recurrence in estrogen receptor-positive and node-negative breast cancer. Retrospective studies and the Trial Assigning Individualized Options for Treatment (TAILORx; ClinicalTrials.gov NCT00310180) validated its significance besides testing chemotherapy benefit in patients with midrange RS (11-25). However, unclarity remains as to whether RS has comparable prognostic value for overall survival (OS) in the TAILORx trial population. Methods: Association between the recurrence scores (midrange or high-range 26-100 vs. low-range 0-10) and OS was evaluated in all eligible patients with clinicopathological and treatment information by multivariable Cox proportional hazards regression model including RS, tumor size, tumor grades, chemotherapy, endocrine regimens, surgery type, progesterone receptor and demographics. We also evaluated the association between RS and invasive disease-free survival (DFS), recurrence-free interval (RFI) or distant recurrence-free interval (dRFI) by multivariable Cox analysis. Results: Median follow-up was 95.5 (range 0.1 to 138.6) months for OS, 89.6 months (range 0 to 134.8) for DFS, 87.7 (range 0 to 134.8) months for RFI or 87.6 (range 0-134.8) months for dRFI. Compared with low score group, midrange and high-range scores were associated with RFI and dRFI, respectively (P≤0.01 each). However, midrange score was neither associated with OS (adjusted HR 1.15; 95% CI 0.87-1.52; P=0.33) nor associated with DFS (HR 1.16; 95% CI 0.97-1.38; P=0.11). High-range score was associated with DFS (HR 1.58; 95% CI 1.21-2.06; P&amp;lt; 0.01) and had a trend towards association with OS (HR 1.44; 95% CI 0.95-2.19; P=0.08). Conclusions: The data indicate that the recurrence scores provide independent prognosis for breast cancer recurrence at both distant and locoregional sites and for distant recurrence, respectively. High-range score is prognostic of disease-free survival, with the midrange score showing marginal association. Midrange and high-range recurrence scores do not provide independent prognostic information for overall survival in hormone receptor-positive, HER2-negative, node-negative breast cancer in the TAILORx trial population. Citation Format: Sherry X. Yang, John Yu, Molin Wang. Association of 21-gene recurrence score with overall survival in phase 3 TAILORx trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-11-09.

Linking clinical and population-based data in older patients with cancer in Belgium: Feasibility and clinical outcomes

IntroductionGeriatric screening and geriatric assessment (GS/GA) have proven their benefits in the care for older patients with cancer. However, less is known about the predictive value of GS/GA for outcomes. To research this, clinical data on GS/GA can be enriched with population-based data. In this article we describe the methods and feasibility of data linkage, and first clinical outcomes (GS/GA results and overall survival). Materials and MethodsA large cohort study consisting of patients aged ≥70 years with a new cancer diagnosis was established using linked data from clinical and population-based databases. Clinical data were derived from a previous prospective study where older patients with cancer were screened with G8, followed by GA in case of an abnormal result (GS/GA study; 2009–2015). These data were linked to cancer registration data from the Belgian Cancer Registry (BCR), reimbursement data of the health insurance companies (InterMutualistic Agency, IMA), and hospital discharge data (Technical Cell, TCT). Cox regression analyses were conducted to evaluate the prognostic value of the G8 geriatric screening tool. ResultsOf the 8067 eligible patients with a new cancer diagnosis, linkage of data from the GS/GA study and data from the BCR was successful for 93.7%, resulting in a cohort of 7556 patients available for the current analysis. Further linkage with the IMA and TCT database resulted in a cohort of 7314 patients (96.8%). Based on G8 geriatric screening, 67.9% of the patients had a geriatric risk profile. Malnutrition and functional dependence were the most common GA-identified risk factors. An abnormal baseline G8 score (≤14/17) was associated with lower overall survival (adjusted HR [aHR] = 1.62 [1.50–1.75], p < 0.001). DiscussionLinking clinical and population-based databases for older patients with cancer has shown to be feasible. The GS/GA results at cancer diagnosis demonstrate the vulnerability of this population and the G8 score showed prognostic value for overall survival. The established cohort of almost 8000 patients with long-term follow-up will serve as a basis in the future for detailed analyses on long-term outcomes beyond survival.

Prognostic value of systemic immune-inflammation index in non-metastatic clear cell renal cell carcinoma with tumor thrombus.

This study aims to determine the prognostic value of SII for non-metastatic clear cell renal cell carcinoma (ccRCC) patients with venous tumor thrombus (VTT). We retrospectively collected and analyzed 328 non-metastatic ccRCC patients with VTT who underwent radical nephrectomy and thrombectomy from 3 tertiary centers in China between 2011 to 2021. Kaplan-Meier analyses and Cox proportional hazard analyses were used to determine its prognostic value for overall survival (OS) and disease free survival (DFS). The Harrell concordance index (C-index), receiver operating characteristic curve (ROC) analysis, and decision curve analysis (DCA) were used to evaluate its role in the improvement of prognostic accuracy of the existing models. Nomogram models containing the SII were then developed and evaluated by R. Patients were divided into low-SII and high-SII groups based on the SII optimal cut-off value 912 calculated by the Youden index in all patients. Higher SII was correlated with more symptoms, longer surgical time, higher WHO/ISUP grade, and longer tumor diameter. Kaplan-Meier analyses revealed significant differences in OS and DFS between two groups. Multivariate analyses revealed that SII was an independent prognostic factor for OS (HR:2.220, p=0.002) and DFS (HR:1.846, p=0.002). Compared with other indicators, SII had a superior accuracy (c-index=0.630 for OS and 0.595 for DFS). It also improved the performance of models for predicting OS and DFS (all p <0.01). Based on the results of LASSO Cox regression analysis, we constructed a nomogram to predict OS and it performed well on both the training cohort (AUC=0.805) and the validation cohort (AUC=0.795). Risk stratification based on nomogram can distinguish patients with different risks (all p <0.001). Preoperative SII is an independent predictive factor for OS and DFS of non-metastatic ccRCC patients with VTT. It can be used to improve the performance of current risk models.