Univariate Cox Research Articles

Nomograms for predicting survival in patients with HER2 negative breast cancer.

e12528 Background: It is increasingly recognized that there is considerable heterogeneity in HER2-negative breast cancer. The clinicopathological characteristics differed between HER2-low and HER2-0 breast cancer evaluated by immunohistochemistry (IHC) or in situ hybridization (ISH). HER2-low breast cancer may benefit from novel antibody-drug conjugates. However, the immunohistochemical agreement of HER2-low is poor. We aimed to construct nomograms to predict the survival of HER2-negative breast cancer and to evaluate the effects of HER2 on survival at the RNA transcript level. Methods: A retrospective analysis was performed on breast cancer patients who were evaluated HER2-negative by IHC or ISH in the TCGA database. Univariate and multivariate cox regression analysis was used to evaluate whether the HER2 RNA transcript level and clinical parameters were independent predictors for overall survival (OS), progression-free survival (PFS), and Disease-Specific Survival (DSS), and nomograms were generated for the prediction of 1-, 2-, 3-, 5-year OS, PFS, and DSS based on significant parameters. Survival curves were drawn using the Kaplan-Meier methods to compare mortality outcomes according to HER2 RNA transcript level (75% vs. 25%). Results: A total of 769 HER2-negative patients were included in the analysis. The median age of patients was 56 years (range 26-30), and the majority were White (80.3%). Univariate and multivariate cox regression analysis showed that age, pN_stage, and pM_stage were independent predictors for OS, but HER2 was not. The C-index of a nomogram based on these three parameters was 0.723 (95%CI, 0.6555-1). HER2, pT_stage, pN_stage, and pM_stage were analyzed as independent predictors of PFS. HER2, pN_stage, and pM_stage were independent predictors of DSS. The C-indexes of established nomograms were 0.734 (95%CI, 0.672-1) and 0.775 (95%CI, 0.686-1) respectively. PFS and DSS were significantly better for patients with high HER2 RNA transcript levels (PFS, log-rank p = 0.00446, HR = 0.352; DSS, log-rank p = 0.0119, HR = 0.247). Conclusions: In the TCGA database, the HER2 RNA transcript level was an independent predictor for PFS and DSS in HER2-negative breast cancer. Stratification of patients at the RNA level can help clinicians optimize treatment for HER2-negative breast cancer.

A Prognostic Model Based on Metabolism-Related Genes for Patients with Ovarian Cancer.

Metabolism-related genes were extracted from the Cancer Genome Atlas (TCGA) database. Through univariate COX and lasso regression models, a dynamic risk model based on MAGs was established. Compared with other clinical factors, demonstrated the ability of the model to predict the prognosis of patients with OC. The clinical samples were used to verify the expression of these MAGs. A metabolism-associated gene signature was constructed by LASSO Cox regression analysis in OC, which was composed of 3-MAGs (PTGIS, AOC3, and IDO1). The signature was used to classify the OC patients into high-risk and low-risk groups. The overall survival of the low-risk group was significantly better than that of the high-risk group. The analysis of the therapeutic effect of bevacizumab showed that bevacizumab was not conducive to improving the prognosis of the low-risk group. We constructed a prognostic model of MAGs in OC, which can be used to predict the prognosis of OC patients and may have a good guiding significance in the individualized treatment of patients.

Effect of autologous lymphocytes combined with chemotherapy as the first-line treatment of advanced gastric cancer.

4037 Background: To evaluate the safety and initial efficacy of adoptive cell therapy (ACT) combined with SOX in first-line treatment of locally advanced unresectable or metastatic gastric adenocarcinoma/gastroesophageal adenocarcinoma. Methods: In this single-arm, single-center exploratory trial, patients with histologically confirmed locally advanced unresectable or metastatic gastric adenocarcinoma/gastroesophageal adenocarcinoma were randomly assigned (1:1) to receive ACT in combination with S-1 and oxaliplatin (SOX) or SOX alone. The primary endpoint was the incidence of adverse events (AEs). Secondary endpoints were progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and disease control rate (DCR). Results: Fifty-nine patients were enrolled in the study between November 20, 2014 and September 6, 2017. 31 patients received ACT combined with SOX (ACT-SOX) and 28 patients received SOX. The most common AEs in both groups were gastrointestinal reaction, leucopenia, neutropenia, anemia, thrombocytopenia, hyperbilirubinemia and elevated aspartate transaminase concentration, with a higher incidence in the SOX group. The median PFS for ACT-SOX and SOX were 6.9 and 4.9 months respectively (HR 0.80, p=0.45), and the median OS were 17.8 and 9.75 months (HR 0.76, p=0.34). Patients who received more than three injections of specific lymphocyte subsets benefited the most from combination therapy. Cox univariate and multivariate analysis showed that tumor metastasis to more than two organs was the main risk factor for PFS and OS. 29 patients in the ACT-SOX group and 25 in the SOX group had measurable lesions. The ORR of ACT-SOX group and SOX group was 55.2% and 32.0%, and DCR of two groups was 93.1% and 88.0%. Conclusions: The safety of ACT-SOX in first-line treatment of patients with locally advanced unresectable or metastatic gastric adenocarcinoma/gastroesophageal adenocarcinoma is good. Compared with SOX alone, although the PFS and OS of ACT-SOX did not reach statistical difference, it could further extend the time of PFS and OS, and the absolute improvement time of OS was about 8.05 months. Continuous benefit of ACT-SOX was observed through long-term follow-up. Clinical trial information: NCT02504229 .

The Prognostic Impact of Log Odds of Positive Lymph Nodes on Survival of Patients With Early-stage Non-small Cell Lung Cancer: A Population Study Based on the Seer Database and a Chinese Cohort

Objective The purpose of this study was to investigate the prognostic value of log odds of positive lymph nodes (LODDS) in patients with early-stage non-small cell lung cancer (NSCLC). Methods Four hundred and eighty-seven NSCLC patients with pT2N0M0 who underwent radical resection from June 1999 to September 2009 at Sun Yat-Sen University Cancer Center and 8,702 patients from the Surveillance, Epidemiology, and End Results (SEER) were reviewed. According to the X-tile analysis, the patients were classified into two groups based on their log odds ratio [≤ –1.40 (group LODDS1) and > –1.40 (group LODDS2)]. Cox univariate and multivariate analyses were used to identify the prognostic factors for survival. Result Patients were divided into two groups according to the value of LODDS: ≤ – 1.40 (group LODDS1) and > – 1.40 (group LODDS2). For the development cohort, the 5-year CSS rate for patients was 79.6% and 69.3% in the group LODDS1 and LODDS2, respectively ( P = .009). For the validation cohort, the 5-year CSS rate was 85.4% for patients in group LODDS1, compared with 82.5% for those in group LODDS2 ( P = .006). In multivariate analysis, LODDS was associated with CSS significantly [hazard ratio (HR), 1.487; 95% confidence intervals (CI), 1.126–1.963] in the development cohort. The HR value of LODDS for CSS was 1.260 (95% CI,1.107–1.434) in the validation cohort. Conclusion LODDS was a strong independent prognostic factor for early-stage NSCLC.

Liver directed therapies in primary and metastatic liver cancer: A rural academic institution experience.

e16188 Background: Liver-directed therapies (LDT) are well established in the treatment of primary and secondary hepatic malignancies and are developed for potentially curative intent, bridging for definitive therapy or palliation. They are used either in isolation usually for hepatocellular carcinoma (HCC) or in combination with systemic chemotherapy and/or surgery. We conducted a retrospective study at our academic institution that serves ethnic minorities and patients with high BMI and multiple major co-morbidities. Methods: All patients who underwent liver-directed therapy at ECU Health Medical Center from the year 2010 to 2020 were included in this study. Total of 196 patients were identified of which 96 met the eligibility criteria. That criteria included all patients who have undergone any type of liver directed therapy in primary and mainly metastatic gastrointestinal liver cancer. We conducted descriptive univariate analysis, cox regression and Kaplan-Meier survival analysis. Results: The study cohort had 63% (n=60) with primary HCC and 38% (n=36) with metastatic liver cancer predominantly colorectal cancer. Median age at diagnosis was 68 yrs. (65.3-69.5), 58% were Caucasian, 38% were black and 2% were other ethnic groups. 68% of the patient were male and 31% were female. ECOG performance status of 1 in 60% of the cohort. 50% of the cohort had 3 major comorbidities other than cirrhosis and hepatitis. Mean body mass index (BMI) was >25 kg/m2. 43% of the patient (n=41) had multiple barriers to care. Patients with primary HCC, 45% had hepatitis C and 48 % had non-viral causes in 60 patients. Child- Pugh A in 67% (n=40), B in 30% (18) and C in 3% (n=3). 70% of non-HCC cohort has colorectal and cholangiocarcinoma. All patient in non-HCC group received chemotherapy and 52% of HCC cohort received systemic therapy. 55% (n= 43) of the patients underwent Y-90 and 55% (n= 53) underwent other types of liver directed therapies, most common being TACE. 62% of the patient underwent 1 treatment and 38% had >2 LDT. Multivariate analysis showed that age (p-value, 0.0229) and type of liver directed therapy ( p-value, 0.0212) are statistically significant in the HCC cohort. In the non-HCC cohort, patients with high BMI (P-value=0.0050) had poor outcome and was statistically significant. Conclusions: Liver directed therapy is a reasonable option for patients with HCC and non-HCC metastatic disease. According to our study, it improves median survival in non-HCC patients. It includes rural population with high BMI, major comorbidities and multiple barriers to care. In this study, 38% of patients were African Americans who are usually underrepresented in majority of studies. Limitations of the study include retrospective nature of the analysis and heterogenous group. In future clinical trials, ethnic minorities should be equally represented to advance health equity and to apply real word data to the populations we serve.

Does low-grade follicular lymphoma with high proliferation index require a different treatment strategy? A single center experience.

e19537 Background: Follicular lymphoma is the most common indolent non-Hodgkin lymphoma (NHL). It accounts for 35% of all NHL. FL is divided into three grades based on the proportion of centroblasts. The clinical aggressiveness increases from grade 1 to 3a, but this does not translate to a different therapeutic approach. Some FL patients have a high proliferation index despite having low grade. We assume patients with high proliferation index FL have a more aggressive disease requiring a different therapeutic approach. Here, we examine this theory in a cohort of 145 patients with follicular lymphoma. Methods: This is a retrospective study of patients diagnosed with FL between 01/01/2011 to 12/31/2021. Patients with histological grade 1-3a and reported proliferation index were included. Low grade is defined as grades 1 and 2. A high grade is defined as grade 3a. A high proliferation index (PI) is defined as Ki67 ≥ 30%. Patients were divided into three groups: low grade/high PI (LG/HP), low grade/low PI (LG/LPI), and high grade (HG). Variables collected included age, gender, race, Ann Arbor staging, PET SUV max, FLIPI score, and treatment details. The primary endpoint is progression-free survival. Secondary endpoints include overall survival (OS) and time to first treatment. Univariate and multivariate Cox regression models were used to analyze predictors of PFS. Survival estimates were calculated using the Kaplan-Meier method and compared using the Log-rank test. Results: We identified 145 patients with follicular lymphoma. The median age was 64. The majority were males (54.5%), whites (94.5%) and had Ann Arbor stage of 3 (42.8%). The median SUV max was 10.6. More than half of the patients were in the LG/LP (60%) compared with LG/HP (22.1%) and HG (17.9%). The median follow-up was 48.7 months. Male gender (HR 1.88, CI 1.04-3.4, p 0.03), Ann Arbor stage 3 (HR 4.3, CI 1.0-18.5, p 0.48) and 4 (HR 8.1, CI 1.9-34.8, p 0.005), PET SUVmax (HR 1.06, CI 1.9-1.1, p 0.001), and grade 3 disease (HR 2.2, CI 1.1-4.2, p 0.02) were associated with increased risk of progression. However, on multivariate analysis, only stage 4 (HR 13.1, 95% CI 1.7-104.0, p 0.02) was associated with an increased risk of progression. Adjusted 4-year PFS was 76% for LG/LP, 71% for LG/HG, and 49% for HG. There was no difference in median OS or time to treatment initiation. Conclusions: Our analysis showed that the median PFS for LG/HP patients is numerically worse than LG/LP, but it did not reach statistical significance. In contrast to previous reports, the trajectory of LG/HG is closer to LG/LP group rather than the HG group. Although outcomes are slightly worse for LG/HP compared with LG/LG, it does not justify a different treatment approach. However, a closer follow-up is warranted. Our study is limited by its retrospective nature and its inherent bias; using cox regression model to adjust for baseline characteristics would help mitigate this bias.

Prognostic risk stratification of low-grade serous ovarian cancer: Model development and validation based on machine learning algorithm.

e17569 Background: Low-grade serous ovarian cancer (LGSOC) is a rare ovarian tumor that lacks a prognostic prediction model. We attempted to construct a clinical nomogram to predict the recurrence and survival of patients with LGSOC. Methods: A multicenter clinical cohort of 199 patients with pathologically confirmed LGSOC was constructed. The predictive model factors were recurrence and survival related clinical factors, which were determined by univariate and multivariate COX regression analysis. The area under receiver operating characteristic curve (AUC), and calibration curve were used to assess the accuracy and discrimination of the nomogram. The concordance index(C-index), net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to evaluate the efficacy of nomogram and FIGO staging in predicting recurrence and survival. Results: A total of 155 patients were included, and four independent prognostic factors were identified to construct the prediction model. The AUC ( > 0.8) showed satisfactory discriminative ability of the nomogram, and the calibration curve showed good agreement between the predicted outcome and the actual outcome. The C-index (PFS: 0.791 vs 0.693; OS: 0.808 vs 0.674), NRI values (0.181 for 3-year and 0.278 for 5-year OS prediction) and IDI values(0.141 for 3-year and 0.147 for 5-year OS prediction, 0.089 for 3-year and 0.079 for 5-year PFS prediction) results showed that nomogram performed better than FIGO staging in predicting prognosis(p < 0.01). Conclusions: We constructed and validated clinical nomogram to individually predict recurrence and survival outcomes in patients with LGSOC, which can help evaluate the prognosis of patients.

Characterizing outcomes in severe cytopenias by 3 months in BCMA and CD19 CAR-T cell therapies: A single institution experience.

e19504 Background: Chimeric antigen receptor (CAR) T-cell therapy is approved for treatment in relapsed/refractory diffuse large B cell lymphoma, penta-refractory multiple myeloma (MM), and acute lymphoblastic leukemia. We evaluated relapse and survival rates by 3 months (mo) in patients (pts) who received BCMA and CD19 CAR-T cell therapies. Methods: We performed a retrospective analysis of pts with RRMM and R/R Non-Hodgkin lymphoma (NHL) who received CAR-T cell therapy from 2012-2023 at the Winship Cancer Institute at Emory University. Pts who relapsed prior to 3mo were excluded. SAS was used for statistical analysis with alpha of 0.05. Grades 3/4 cytopenias were compared at day 0, 1mo, and 3mo per CTCAE criteria with each pt counted once if > 1 cytopenia. Hematological recovery was defined as sustained Hgb > 8, Plt > 50,000, and ANC > 1000 without transfusion support. Group differences were evaluated using Chi-Square or Fisher’s exact tests for categorical and ANOVA or Kruskal-Wallis for numerical variables. Overall survival (OS) and progression-free survival (PFS) were determined using the Kaplan-Meier method from CAR-T receipt to progression or death, or last known contact for those censored. Univariable and multivariable cox regression were performed. Results: Of 126 pts, 60 had MM and 66 had NHL. Median age at CAR-T receipt was 64yrs (range: 25-85). Fifteen pts had ECOG ≥2. Most pts were male (52.4%) and of white race (61.9%). For R/R NHL, 39.4% received tisa-cel, 33.3% axi-cel, 13.6% brexu-cel, 3.0% liso-cel and 10.6% clinical trial. For RRMM, 91.7% received ide-cel and cilta-cel (8.3%). Bridging therapy, CRS, and ICANS were not associated with severe cytopenias. Overall, 89.7% had grade 3/4 cytopenias at day 0, 54.0% at 1mo, and 34.1% at 3mo. Cytopenia rates, hematological recovery, transfusions, and infectious complications were comparable between groups. Overall, 36.5% required GCSF, 34.9% red cells, 23.0% platelets, and 2.4% TPO. In MM pts, decreased OS was seen with persistence of severe cytopenias (p = 0.009) and decreased PFS with GCSF use ≥2wks (p = 0.007). Time to ANC recovery (days) was more prolonged in MM compared to NHL pts (p = 0.039). Overall median time to recovery (days) was 8, 19, 22.5 for Hgb, ANC, and Plt respectively. On MVA for overall cohort, grade 3/4 cytopenias at 3mo were associated with decreased OS [HR 2.28, 95%CI: (1.22-4.29), p = 0.010) and PFS [HR 1.8, 95%CI: (1.09-2.98), p = 0.022]. On MVA for NHL, decreased OS [HR 2.38, 95%CI: (1.03-5.48), p = 0.043] and PFS [HR 2.11, 95%CI: (1.01-4.41), p = 0.047] were associated with 3mo grade 3/4 cytopenias but not seen in MM pts. Conclusions: We report significant rates of severe cytopenias at 3 months and a potential association with higher relapse and decreased survival rates in pts receiving BCMA and CD19 CAR-T cell therapies. These results are hypothesis generating, and more prospective studies are needed for further confirmation.

Construction and Identification of an NLR-Associated Prognostic Signature Revealing the Heterogeneous Immune Response in Skin Cutaneous Melanoma.

Skin cutaneous melanoma (SKCM) is the deadliest dermatology tumor. Ongoing researches have confirmed that the NOD-like receptors (NLRs) family are crucial in driving carcinogenesis. However, the function of NLRs signaling pathway-related genes in SKCM remains unclear. To establish and identify an NLRs-related prognostic signature and to explore its predictive power for heterogeneous immune response in SKCM patients. Establishment of the predictive signature using the NLRs-related genes by least absolute shrinkage and selection operator-Cox regression analysis (LASSO-COX algorithm). Through univariate and multivariate COX analyses, NLRs signature's independent predictive effectiveness was proven. CIBERSORT examined the comparative infiltration ratios of 22 distinct types of immune cells. RT-qPCR and immunohistochemistry implemented expression validation for critical NLRs-related prognostic genes in clinical samples. The prognostic signature, including 7 genes, was obtained by the LASSO-Cox algorithm. In TCGA and validation cohorts, SKCM patients with higher risk scores had remarkably poorer overall survival. The independent predictive role of this signature was confirmed by multivariate Cox analysis. Additionally, a graphic nomogram demonstrated that the risk score of the NLRs signature has high predictive accuracy. SKCM patients in the low-risk group revealed a distinct immune microenvironment characterized by the significantly activated inflammatory response, interferon-α/γ response, and complement pathways. Indeed, several anti-tumor immune cell types were significantly accumulated in the low-risk group, including M1 macrophage, CD8 T cell, and activated NK cell. It is worth noting that our NLRs prognostic signature could serve as one of the promising biomarkers for predicting response rates to immune checkpoint blockade (ICB) therapy. Furthermore, the results of expression validation (RT-qPCR and IHC) were consistent with the previous analysis. A promising NLRs signature with excellent predictive efficacy for SKCM was developed.

PROGNOSTIC IMPACT OF RENIN ANGIOTENSIN ALDOSTERONE SYSTEM INHIBITOR IN HYPERTENSIVE PATIENTS UNDERGOING TRANSCATHETER AORTIC VALVE IMPLANTATION

Objective: The purpose of this study was to determine the prognostic impact of baseline treatment with RAAS inhibitors (RAASi) on all-cause mortality in a population of patients with severe AS who underwent transcatheter aortic valve implantation (TAVI). Design and method: The study included 373 patients with AS who had undergone TAVI. Analyses were undertaken on the subgroup of hypertensive individuals (n 327) with 2 years of follow-up. Clinical characteristics were compared using Kruskal-Wallis non-parametric test for independent samples and study-stratified multivariable Cox proportional hazards regression models was built according to baseline RAASi therapy status. A second analysis was undertaken by categorizing patients receiving RAASi medication (n 222) into those receiving angiotensin II receptor blockers (ARBs) (n 110) and those receiving angiotensin-converting enzyme inhibitors (ACEi) (n 112). Results: Taking RAASi at baseline in the hypertensive patients group was significantly related to gender (Women 56,8%), heart failure (25,7%), chronic kidney disease (CKD) (25,7%), atrial fibrillation (AF) (19,4), being on calcium-channel blocker (26,6%) or anti-platelet therapy (68,5%) (all p < 0,05). All-cause mortality occurred in 23 (10,4%) of the patients on RAASi, 9 (8,2%) on ARBs and 14 (12,4%) on ACEi. In univariate COX regression model treatment with a RAASi was related with a reduction in 2-year all-cause mortality (EXP 0.46, p 0.011). After multivariable correction for significant confounders the association was not statistically significant (p = 0.08). Analyzing ACEi ARBs separately baseline ARB therapy was associated with significant reduction in all-cause mortality (EXP 0.44, p 0.028) (Figure) that was confirmed in multivariate analysis (EXP 0.42, p 0.038) with no impact in baseline ACEi use (Table). Heart failure (EXP 2.87, p < 0.001), atrial fibrillation (EXP 2.39, p 0.005) and chronic kidney disease (EXP 2.08, p 0.02) were all related with an increased 2-year all-cause mortality, but after multivariable correction only heart failure remained statistically significant. Conclusions: ARBs, but not ACEi, are independently associated with a decreased risk of 2-year all-cause death in a cohort of hypertensive patients with severe AS who underwent TAVI. While it is true that these results have molecular basis, additional research is required to corroborate these findings.

Radiation-sensitive genetic prognostic model to identify individuals at risk for radiation resistance in head and neck squamous cell carcinoma.

e18042 Background: The advantages of radiotherapy for head and neck squamous cell carcinoma (HNSCC) depend on the radiation sensitivity of the patient. Here, we established and verified radiological factor-related gene signature and built a prognostic risk model to predict whether radiotherapy would be beneficial. Methods: Data from The Cancer Genome Atlas, Gene Expression Omnibus, and RadAtlas databases were subjected to LASSO regression, univariate COX regression, and multivariate COX regression analyses to integrate genomic and clinical information from patients with HNSCC. HNSCC radiation-related prognostic genes were identified, and patients classified into high- and low-risk groups, based on risk scores. Variations in radiation sensitivity according to immunological microenvironment, functional pathways, and immunotherapy response were investigated. Results: We built a clinical risk prediction model comprising a 15-genes signature and used it to divide patients into two groups based on their susceptibility to radiation: radiation-sensitive and radiation-resistant. Overall survival was significantly greater in the radiation-sensitive than the radiation-resistant group. Further, our model was an independent predictor of radiotherapy response, outperforming other clinical parameters, and could be combined with tumor mutational burden, to identify the target population with good predictive value for prognosis at 1, 2, and 3 years. Additionally, the radiation-resistant group was more vulnerable to low levels of immune infiltration, which are significantly associated with DNA damage repair, hypoxia, and cell cycle regulation. Tumor Immune Dysfunction and Exclusion scores also suggested that the resistant group would respond less favorably to immunotherapy. Conclusions: Our prognostic model based on a radiation-related gene signature has potential for application as a tool for risk stratification of radiation therapy for patients with HNSCC, helping to identify candidates for radiation therapy and overcome radiation resistance.

Predicting immunotherapy outcomes of melanoma patients before treatment by intestinal microbiota.

e21512 Background: To find the appropriate patients that can benefit from immunotherapy is very important in precision medicine. Biomarkers such as PD-L1, TMB and MSI attracted a lot of attentions in immunotherapy. Emerging biomarkers such as intestinal microbiota and others also showed promising predictive/prognosis values in the clinical studies. The purpose of this study was to evaluate new prediction models based on intestinal microbiota data from the melanoma patients before treatment. Methods: This study enrolled 41 microbiome 16S patients from published datasets. Firstly, survival analysis was performed on the response group (R) and non-response group (NR). Species in all the samples were included to perform univariate cox regression analysis, and the differences of intestinal microbiota between R and NR groups were evaluated by alpha and beta diversities. The specific differential microbiota was obtained by Student's t-test and LEfSe and further screened by the best performance of the five machine learning methods. To find the minimum set of the microbiota species, logistic regression and ROC curve were used. Analyses of KO data included PCA, differential and KEGG enrichment analysis. Significantly enriched pathways were scored by ssGSEA. The spearman correlations between ssGSEA scores and final microbiota species were calculated. Results: The non-response (NR) group had shorter PFS. Univariate cox regression analysis on all the samples identified 36 species which might be associated with prognosis. Alpha and beta diversities showed the R and NR groups were significantly different. Student's t-test identified 52 differential species and LEfSe identified 72 OTUs. Most of the microbiome enriched in R group belonged to firmicutes, while those enriched in NR group belonged to firmicutes, bacteroides and proteobacteria. We then constructed five machine learning models to predict PD1 immunotherapy responses of the melanoma patients and finally identified 25 species. Logistic regression and ROC curve identified the minimum set of the microbiota species including methanobrevibacter smithii, schaalia odontolytica, cuneatibacter caecimuris. A total of 119 differentially expressed KO genes were obtained by differential analysis, and those genes were mainly enriched in 25 pathways. Spearman correlation analysis found that those three microbial species were mainly associated with 12 pathways which might influence the classification of the two groups. Conclusions: In this study we identified three microbial species which might contribute to the classification of the R and NR patient groups. The models based on intestinal microbiota data can predict immunotherapy outcomes of melanoma patients.

Identification of DNA Damage Repair Gene Signature as a Novel Prognostic Marker in Glioblastoma Multiforme

The therapeutic efficacy of Glioblastoma multiforme (GBM) is limited. The effect of the DNA damage repair is an important factor. The expression data was downloaded from the TCGA (training dataset) and GEO (external dataset) database. The univariate cox regression analysis and Least absolute shrinkage and selection operator (LASSO) was used to constructed a DNA damage repair (DDR) gene signature. The receiver operating characteristic (ROC) analysis and Kaplan-Meier (KM) curve analysis were employed to estimate the prognostic value of the risk signature. Moreover, the consensus clustering analysis was used to investigate the potential subtypes of the GBM based on the DDR expression. We constructed a three DDR-related gene signature through the survival analysis. The K-M curve result suggesting that patients in the low risk group have a significantly better survival outcome than high risk group in the training dataset and external validation dataset. The ROC analysis result indicated that the risk model has a high prognostic value in the training and external validation dataset. Moreover, three stable molecular subtypes were identified and validated in the GEO database and TCGA database based on the expression of DNA repair gene. The microenvironment and Immunity of GBM was further investigated and discovered that Cluster 2 group have a higher immunity and immune score, compared with other two clusters. In conclusion, the DNA damage repair-related signature was an independent and powerful prognostic biomarker in GBM. The subtype for the GBM may have important implications in the sub-classification of GBM.

Multicenter experience with radiotherapy for relapse after chimeric antigen receptor T cell therapy in non‐Hodgkin lymphoma

Introduction: Approximately half of patients relapse following chimeric antigen receptor T-cell therapies (CAR T), a challenging clinical scenario without established treatment paradigms. Salvage radiotherapy (SRT) may be an important strategy for this population with rapidly growing, often chemotherapy-refractory disease. Limited data are available regarding SRT utilization and outcomes. Methods: We reviewed all patients with Non-Hodgkin Lymphoma treated with SRT for any intent post CAR T from 2016 to 2022 at four US cancer centers. Comprehensive SRT was defined as including all sites with PET avidity > liver max. Failure sites were classified as pre-existing (present pre SRT) versus new, and as in field, marginal (within 1 cm of), or distant with respect to SRT prescription dose region. Toxicities were graded by CTCAE v5.0. Event free and overall survival (EFS/OS) were measured from SRT start by Kaplan Meier. EFS was defined as freedom from progression, initiation of subsequent therapy, or death. Clinicodemographic associations with outcomes were assessed by Cox univariate proportional hazards. Results: 121 patients with diffuse large B cell lymphoma (DLBCL; n = 110), mantle cell lymphoma (n = 8), and primary mediastinal B cell lymphoma (n = 3) were included. Patients received axicabtagene (n = 62), tisagenlecleucel (n = 27), lisocabtagene (n = 17), experimental CAR T (n = 12), and brexucabtagene (n = 3). For 49%, SRT was the first post-CAR T therapy. SRT indications included palliation (n = 72), consolidation (n = 5), bridging to allogeneic transplant (allo; n = 5) or 2nd CAR T (n = 3), and other (n = 33). At SRT, 29 (24%) had localized disease of which 28 were treated comprehensively; overall 37% of SRT was comprehensive. Median dose was 30 Gy (4–50.4). 27% received concurrent systemic therapy. SRT was well tolerated: 8% (n = 10) had ≥ grade 2 (G2) acute adverse events (G3 = 1, no G4/5). Objective response rate was 74% (41% complete) within the SRT field and 38% (22% complete), overall. With a median follow up of 6 mo, 78 patients (64%) progressed. First failure sites were 64% pre-existing/mixed and 38% in field/marginal. For DLBCL patients, median EFS was 4.2 mo in limited stage and 1.2 mo in advanced (p < 0.001). Median OS was 59.6 mo and 3.4 mo in localized and advanced DLBCL relapse (p < 0.001). Median OS for RT as bridging to allo/CAR T, consolidation, and palliation was unreached, 6.7 mo, and 3.0 mo (p < 0.001). Localized relapse and receipt of comprehensive SRT were associated with improved EFS (p < 0.001) while primary refractory disease to CAR T (p = 0.02), elevated LDH pre SRT (p = 0.02), and SRT for palliation (p = 0.03) or for ≥2ndsalvage post CAR T (0.04) were associated with shorter EFS. Keywords: Aggressive B-cell non-Hodgkin lymphoma, Cellular therapies, Radiation Therapy Conflicts of interests pertinent to the abstract. C. Ladbury Research funding: Reflexion G. Shah Consultant or advisory role: ArcellX Research funding: Janssen, Amgen, Beyond Spring, BMS M. D. Jain Consultant or advisory role: Kite/Gilead, Novartis, BMS, MyeloidTx Research funding: Kite/Gilead, Incyte S. Dandapani Research funding: Reflexion, Bayer B. S. Imber Honoraria: GT Medical Technologies Inc.

Immunological signature of patients with thymic epithelial tumors and Good syndrome: Correlation with clinical outcome.

e20648 Background: Thymic epithelial tumors (TETs) are extremely rare and heterogenous neoplasms, associated with immune dysregulation. Recognized prognostic factors are TNM stage and the Masaoka-Koga classification. To the best of our knowledge, no study has been conducted to investigate the correlation between immunophenotype, level of cytokines, chemochines and clinical outcome in TETs patients. The aim of this study was to evaluate the correlation of immunological signature and long-term outcome in patients with TETs and Good Syndrome (GS). Methods: From May 2019 to October 2022, consecutive patients with TETs and GS, referred to the Rare Tumors Coordinating Center of Campania Region (CRCTR) of Federico II of Naples, were enrolled. The immunophenotype of monocytes, neutrophils, eosinophils, CD4+ T cells, CD8 + T cells, B-cells, NK cells and NKT-cells, T regulatory cells, and the evaluation of serum levels of cytokines, chemokines and growth factors were assessed using the 8-color immunophenotyping kit, Treg detection kit and pre-formed Kits by Bioplex multiplex, respectively. D’Agostino-Pearson normality test was used to evaluate whether the continuous data were normally distributed, and a two-tailed t-test for independent samples was used. Overall survival (OS) analysis was performed generating Kaplan-Meier curves and Cox Univariate models for the considered categorical stratifications. p-values &lt; 0.05 were considered statistically significant. Results: A total of 24 consecutive TETs patients were included in the study: 13 (54.17%) patients were male and 11 (48.83%) were female, with a median age of 54.96 ± 9.6 years. Tumor histology included 20 thymoma, and 4 thymic carcinoma. Autoimmune diseases were found in 13 patients all of whom had thymoma. At the time of this analysis, 5 (20.83%) patients had no evidence of disease (NED) by imaging and were in follow-up, 17 (70.83%) patients were still alive. The analysis of leucocytes did not show statistically significant association with clinical outcome of TETs patients. On the contrary, a statistically significant correlation between serum concentration of IL-6 and OS was found with lower levels of IL-6 associated with poorer prognosis (HR: 9.654; p = 0.016). In addition, we found a statistically significant reduction of IL-2 (p = 0.04), IL-15 (p = 0.048), IL-5 (p = 0.03) and VEGF (p = 0.01) serum levels in patients with evidence of disease, as compared to NED patients. Conclusions: Overall, these findings suggest that measurement of IL-6 levels may be a useful parameter for identifying TETs patients with GS who have more aggressive diseases. Our preliminary data may be useful in the clinical management of this complex disease. Further studies are needed to better understand the pathophysiology and clinical implications of immunophenotype alterations in TETs patients.

An ICD-Associated DAMP Gene signature predicts survival and immunotherapy response of patients with lung adenocarcinoma

BackgroundWhile some lung adenocarcinoma (LUAD) patients benefit long-term from treatment with immune checkpoint inhibitors, the sad reality is that a considerable proportion of patients do not. The classification of the LUAD tumor microenvironment (TME) can be used to conceptually comprehend primary resistance mechanisms. In addition, the most recent research demonstrates that the release of damage-associated molecular pattern (DAMP) in TME by immunogenic cell death (ICD) may contribute to the adaptive immune response. Currently, however, there is no such comprehensive research on this topic in LUAD patients. Therefore, we set out to investigate how to reverse the poor infiltration characteristics of immune cells and boost antitumor immunity by identifying DAMP model.MethodsIn this study, ICD-related DAMP genes were selected to investigate their effects on the prognosis of LUAD. To create a risk signature using the TCGA-LUAD cohort, the univariate COX regression and the least absolute shrinkage and selection operator regression were carried out, and the results were verified in a GEO dataset. Subsequently, the multivariate COX regression was applied to establish a prognostic nomogram. And the ESTIMATE and ssGSEA algorithms were utilized to analyze immune activity and the TIDE algorithm was for responsiveness to immunotherapy. Moreover, clinical tissue samples were used to verify the differential expression of 9 DAMP genes in the signature.ResultsWe identified two distinct DAMP molecular subtypes, and there are remarkable differences in survival probability between the two subtypes, and patients with higher levels of DAMP-related genes are “hot tumors” with increased immune activity. In addition, 9 DAMP genes were selected as prognostic signature genes, and clinical outcomes and immunotherapy response were better for participants in the low-risk group. Importantly, according to the area under the curve (AUC) value in evaluating the efficacy of immunotherapy, this signature is superior to existing predictors, such as PD-L1 and TIDE.ConclusionsOur study suggests ICD plays an important part in modeling the TME of LUAD patients. And this signature could be utilized as a reliable predictor to estimate clinical outcomes and predict immunotherapy efficacy among LUAD patients.

Inflammatory Ratios as Survival Prognostic Factors in Resectable Gastric Adenocarcinoma.

The purpose of the study was to assess the relationship between inflammatory biomarkers (NLR-neutrophil-to-lymphocyte ratio, PLR-platelet-to-lymphocyte ratio, LMR-lymphocyte-to-monocyte ratio, SII-systemic immune-inflammation index) and overall survival in gastric cancer patients. Over a six-year period (2016-2021), we conducted a longitudinal retrospective cohort research on 549 patients with resectable stomach adenocarcinoma. The overall survival was determined using the univariate and multivariate COX proportional hazards models. The age of the cohort varied between 30 and 89 years old, with an average age of 64.85 ± 10.51 years. Four hundred seventy-six patients (86.7%) had R0 resection margins. Eighty-nine (16.21%) subjects received neoadjuvant chemotherapy. Two hundred sixty-two (47.72%) patients died during the follow-up period. The median survival time in the cohort was 390 days. A significantly lower (p = 0.029-Logrank test) median survival was observed for R1 resections (355 days) in comparison with R0 resections (395 days). Significant differences in survival were observed regarding tumor differentiation, tumoral (T), and node (N) stage. No differences in survival were observed between the low or high value of inflammatory biomarkers (dichotomized by median value in the sample). In the COX univariate and multivariate regression models, elevated NLR proved an independent prognostic factor for lower overall survival [HR = 1.068, (95% CI 1.011-1.12)]. In this study, the other inflammatory ratios (PLR, LMR, and SII) did not prove as prognostic factors for gastric adenocarcinoma. In resectable gastric adenocarcinoma, elevated NLR before surgery was associated with lower overall survival. PLR, LMR, and SII had no prognostic value for the patient's survival.

Construction of a novel MPT-driven necrosis-related lncRNAs signature for prognosis prediction in laryngeal squamous cell carcinoma.

Mitochondrial permeability transition (MPT)-driven necrosis, a type of programmed cell death, has recently gained much attention in a variety of tumor types. Few studies have been performed to explore the role of MPT-driven necrosis-related lncRNAs (MPTDNRlncRNAs) in laryngeal squamous cell carcinoma (LSCC). The purpose of our study is to screen MPTDNRlncRNAs with prognostic value and to explore their potential roles in LSCC. The RNA-sequencing data and the corresponding clinical data of LSCC patients were obtained from the TCGA database, and those MPT-driven necrosis-related genes were extracted from the Gene Set Enrichment Analysis (GSEA) database. We identified MPTDNRlncRNAs differentially expressed in LSCC. Also, we gained MPT-driven necrosis-related prognostic lncRNAs by univariate cox regressionanalysis. A novel MPTDNRlncRNAs signature was constructed by LASSO-COX. The accuracy and utility of the MPTDNRlncRNAs signature were evaluated via a variety of statistical methods. Multiple bioinformatics tools were used to explore the underlying difference in biological functions and signaling pathways between the different risk groups. The expressions levels of MPTDNRlncRNAs were analyzed using RT-qPCR in LSCC cell line. Finally, we identified A 5 MPTDNRlncRNAs signature in LSCC. Our prognostic model demonstrated an efficient ability to predict outcomes. The proportion difference of immune cells in the subgroups were significant, such as M0 macrophage and T follicular helper cells. The in vitro experiments suggested that our MPTDNRlncRNAs were significantly different. This 5 MPTDNRlncRNAs signature is a prognostic biomarker for LSCC. More importantly, the novel biologic prognostic model can be utilized for personalized immunotherapy in LSCC patients.

Pan-cancer analysis reveals the prognostic and immunologic roles of cereblon and its significance for PROTAC design

BackgroundCereblon (CRBN) has emerged as a vital E3 ubiquitin ligase for Proteolysis-targeting chimera (PROTAC) design. However, few studies focus on the physiological mechanism of CRBN, and more studies are needed to explore the influence of CRBN on tumorigenesis. This pan-cancer analysis aims to explore the prognostic and immunologic roles of CRBN, and provide new insight for CRBN into cancer treatment and PROTAC design. MethodsThe TCGA database, TIMER 2.0 database, and TISIDB database were used to analyze the role of CRBN in pan-cancer. Multiple bioinformatic methods (ssGSEA, Kaplan-Meier, univariate cox regression, ESTIMATE, CIBERSORT) were applied to investigate the CRBN expression status, gene activity, prognostic values, and its correlation with immune scores, immune infiltration, immune-related functions, HALLMARKs functions, and response to immunotherapy in pan-cancer. ResultsIn most cancer types, the expression and activity of CRBN in tumor groups were lower compared with normal groups. Upregulated CRBN expression may indicate a better prognosis for cancer patients. The Immune score, stromal score, and tumor purity varied greatly among different cancer types. GSEA analysis showed that high CRBN expression was correlated with the downregulation of tumor-promoting signaling pathways. The level of CRBN was associated with Tumor mutation burden (TMB), Microsatellite instability (MSI), objective response rate (ORR), and immune cell infiltration in a few cancer types. ConclusionPan-cancer analysis reveals the potential role of CRBN as a prognostic biomarker and versatile immunologic roles in different cancer types. Upregulated expression of CRBN may be beneficial to CRBN-related immunotherapy and PROTAC design.

Analysis of prognostic biomarker models and immune microenvironment in acute myeloid leukemia by integrative bioinformatics.

Acute myeloid leukemia (AML) is a hematological cancer driven on by aberrant myeloid precursor cell proliferation and differentiation. A prognostic model was created in this study to direct therapeutic care. Differentially expressed genes (DEGs) were investigated using the RNA-seq data from the TCGA-LAML and GTEx. Weighted Gene Coexpression Network Analysis (WGCNA) examines the genes involved in cancer. Find the intersection genes and construct the PPI network to discover hub genes and remove prognosis-related genes. A nomogram was produced for predicting the prognosis of AML patients using the risk prognosis model that was constructed using COX and Lasso regression analysis. GO, KEGG, and ssGSEA analysis were used to look into its biological function. TIDE score predicts immunotherapy response. Differentially expressed gene analysis revealed 1004 genes, WGCNA analysis revealed 19,575 tumor-related genes, and 941 intersection genes in total. Twelve prognostic genes were found using the PPI network and prognostic analysis. To build a risk rating model, RPS3A and PSMA2 were examined using COX and Lasso regression analysis. The risk score was used to divide the patients into two groups, and Kaplan-Meier analysis indicated that the two groups had different overall survival rates. Univariate and multivariate COX studies demonstrated that risk score is an independent prognostic factor. According to the TIDE study, the immunotherapy response was better in the low-risk group than in the high-risk group. We eventually selected out two molecules to construct prediction models that might be used as biomarkers for predicting AML immunotherapy and prognosis.