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Haiyong Wang
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P02 - Diagnostics and Interventional Pulmonology (ID 110)
- Event: WCLC 2020
- Type: Posters
- Track: Diagnostics and Interventional Pulmonology
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P02.05 - A Nomogram to Predict Survival in Non-Small Cell Lung Cancer Patients Receiving Atezolizumab: An Analysis of OAK and POPLAR Cohorts (ID 3629)
00:00 - 00:00 | Presenting Author(s): Haiyong Wang
- Abstract
Introduction
In this study, we would like to build a novel nomogram model which could assist clinicians to select right candidates who would benefit from atezolizumab treatment.
Methods
A total of 424 NSCLC patients treated with atezolizumab from the OAK trial were enrolled in the training cohort. In addition, another 144 NSCLC patients receiving atezolizumab from the POPLAR trial were included in the test cohort. Univariate and multivariate Cox regression analyses were applied to analyze the impact of clinical parameters on OS. The ROC curve was applied to assess clinical utility of the nomogram. The calibration curve and C-index was applied to perform the validation of the nomogram. Kaplan-Meier method was used to draw survival curves and compared differences by log-rank test.
Results
Our results showed that race, sex, histopathology, ECOG PS, BLSLD and number of metastasis site were independent prognostic factors for NSCLC patients receiving atezolizumab. Basing on these clinical variables, we built a predictive nomogram model. Then, we classified patients into high- and low-risk group according to the risk classification system generated by the nomogram. Survival curves of the training cohort revealed that patients received atezolizumab in the high-risk group had poorer OS than those in the low-risk group (P < 0.0001). Similarly, consistent result was observed in the test cohort, showing that patients receiving atezolizumab with high-risk had relative worse OS than those with low-risk (P = 0.003). More importantly, we found that no matter in OAK trial or POPLAR trial, either in high-risk or low-risk group, NSCLC patients treated with atezolizumab had better OS compared with those receiving docetaxel (all, P < 0.05).
Conclusion
Basing on inexpensive and easily available clinicopathological parameters, we built a nomogram which revealing a good performance to predict individual OS probability among patients with NSCLC receiving atezolizumab.
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P36 - Pathology - Prognosis (ID 106)
- Event: WCLC 2020
- Type: Posters
- Track: Pathology, Molecular Pathology and Diagnostic Biomarkers
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P36.03 - Identification of Immune-Related lncRNA Clusters and Prognostic Effects for Lung Adenocarcinoma Patients (ID 956)
00:00 - 00:00 | Presenting Author(s): Haiyong Wang
- Abstract
Introduction
Long non-coding RNAs (lncRNAs) can regulate not only the immune response but also remodel the tumor microenvironment in lung adenocarcinoma (LUAD). However, immune-related lncRNAs and their immune and genomic alterations characteristics and prognostic effects for lung adenocarcinoma patients still remain not reported.
Methods
The list of immunoregulatory mRNA data was downloaded from the ImmPort database and the lncRNAs profiles were extracted from the ensembl database. Simultaneously, all RNA sequencing (RNA-seq), somatic mutations, copy number variation (CNV) data of LUAD samples were downloaded from TCGA and GEO. Prognostic analysis was performed on lncRNA by univariate Cox regression. Co-expression network map between immune-related lncRNAs and mRNAs was constructed by cytoscape3.6.0. The 147 immune-related lncRNAs were mapped to the expression profile of LUAD samples to perform consistent clustering by CCP tool. GSVA analysis was performed on different genes to obtain the changes of related pathways. ESTIMATE and CIBERSORT methods were used to estimate the component and immune cells infiltration of the tumor immune microenvironment in LUAD samples. The copy number spectrum of immune-related lncRNAs was extracted by GISTIC 2.0 software. Survival analysis was used to compare the survival curves of different immune-related lnRNA clusters.
Results
Co-expression network map between immune-related lncRNAs and mRNAs in LUAD was constructed and 147 immune-related lncRNAs with significant prognostic value were obtained. Subsequently, 500 LUAD samples were separated into two tumor clusters with different immune phenotypes based on immune-related lncRNAs. Notably, the cluster 2 had higher immune score, and lower tumor purity than the cluster 1. The relative levels of immune cell types in cluster 1 were higher than the cluster 2 , such as Macrophages M0(P=0.002), Macrophages M2(P=0.003), Mast cells activated(P=0.002), Neutrophils(P＜0.001), apart from B cells memory(P=0.004), which was lower in cluster 1. GSVA analysis demonstrated an association between immune-related lnRNA clusters and stem cell/EMT-related gene signatures. The disparities of CNV segments between cluster 1 and cluster 2 were identified, and both the amplified and deleted portions were enriched in cluster 1. The disparities of immune activation-related mutant genes between cluster 1 and cluster 2 were identified, such as KEAP1, TLR4, etc. Survival analysis indicated that immune-related lncRNA clusterization can predict the prognosis of the LUAD patients.
Conclusion
we obtained 147 immune-related lncRNAs in LUAD and identified the characteristics of immune cells infiltration and genomic alterations based on immune-related lncRNA clusters to provide novel perspective for the research of the molecular mechanisms and immunotherapy of LUAD.
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P50 - Small Cell Lung Cancer/NET - Real World Outcomes (ID 232)
- Event: WCLC 2020
- Type: Posters
- Track: Small Cell Lung Cancer/NET
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P50.07 - Fewer Liver and Lymph Node Metastases May Contribute to Survival Benefits for Patients With c-SCLC Compared With SCLC (ID 984)
00:00 - 00:00 | Presenting Author(s): Haiyong Wang
- Abstract
Introduction
SCLC accounts for 15%-20% in all lung cancer.And the World Health Orgnazation (WHO) / International Association for the Study of Lung Cancer (IASLC) classification divides SCLC into two subtypes: pure SCLC and c-SCLC. c-SCLC was defined as SCLC combined with any of non-small cell lung cancer (NSCLC) histologic types. And NSCLC can be squamous cell carcinoma, adnocarcinoma, large cell neuroendocrine carcinoma and so on. In c-SCLC, the combined components may be one or more and currently the most common is SCLC combined squamous cell carcinoma.
The incidence of c-SCLC was much lower than pure SCLC, which may be due to insufficient diagnostic information provided by limited samples such as small biopsy or cytology analysis. Previous studies indicated that the prognosis of c-SCLC was different from pure SCLC and this showed that c-SCLC may have distinct biological behavir compared with pure SCLC. However, most previous studies about SCLC only focused on pure SCLC or made them as a whole instead of distingushing them as two types.
At present, given the few studies on c-SCLC, we mainly aimed to compare the clinicopathological characteristics and prognosis differences between patients with c-SCLC and SCLC.
Methods
We screened a total of 400 patients diagnosed with c-SCLC and 20841 patients with SCLC between 2010 and 2015 from SEER database. The chi-square test was used to compare patient baseline characteristics differences between c-SCLC and SCLC. Propensity Score Matching (PSM) was used to eliminate any bias between patients with c-SCLC and SCLC. Logistic regression was used to identify independent risk factors for c-SCLC and SCLC patients. In addition, univariate and multivariate Cox proportional hazards regression models were used to analyze the influence of different variables on overall survival (OS).
Results
Our result revealed that the OS of c-SCLC patients was significantly better than that patients with SCLC before PSM (P < 0.001). Further multivariable analysis showed that liver metastasis (HR: 1.218; 95% CI: 0.858-1.729; P = 0.269) and lung metastasis (HR: 1.057 ; 95% CI: 0.729-1.534; P = 0.768) were not significant and independent factors on c-SCLC patients’ survival. Then, we conducted PSM to eliminate bias between patients with c-SCLC and SCLC. However, the result showed that there was no significant difference on OS between c-SCLC and SCLC patients after PSM (P = 0.789). Multivariate logistic regression analysis revealed that the risk of N metastasis (OR: 0.555; 95% CI: 0.439-0.703; P < 0.001) and liver metastasis (OR: 0.591; 95% CI: 0.448-0.779; P < 0.001) was lower for c-SCLC patients compared with SCLC patients.
Conclusion
c-SCLC patients’ prognosis was better than that of SCLC patients, which may be due to fewer liver and lymph node metastases at the time of diagnosis. However, if we limited the clinical variables, there was no difference in survival between c-SCLC and SCLC patients.
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P52 - Staging - Prognosis and Staging (ID 186)
- Event: WCLC 2020
- Type: Posters
- Track: Staging
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P52.09 - Proposals for Revision of N Descriptors in the Forthcoming Edition of TNM Staging for NSCLC (ID 988)
00:00 - 00:00 | Presenting Author(s): Haiyong Wang
- Abstract
Introduction
The nodal status is an important factor to guide treatment and determine prognosis for patients with non-small cell lung cancer (NSCLC). The current revised 8th edition TNM staging defines pathological nodal (pN) classification based only on the location of lymph nodes (LNs). It remains the same as the previous edition which has some limitations to assess the prognosis in heterogeneous pN1 and pN2 cases.
The number of LNs (nN) have been reported to be a critical prognostic factor in NSCLC patients. And nN staging has been included in the TNM staging system for breast, gastric and colorectal cancer. Our previous studies have shown that nN included in the staging could better reflect the prognosis for patients with NSCLC. However, the previous research has some deficiencies in the source of patients and statistical methods.
Therefore, in this present study, we integrated patients from the SEER database and Shandong Cancer Hospital and Institute, Shandong Provincial Hospital to validate the prognostic advantage for NSCLC patients combined pN and nN stage.
Methods
According the 6th and 7th edition of TNM staging, 5779 and 8231 NSCLC patients from the SEER database were collected in this study. A total of 385 NSCLC patients were included in the validation cohort. Of them, 157 patients were from Shandong Provincial Hospital and the rest were from Shandong Cancer Hospital and Institute. X-tile model was used to determine the optimal cutoff value of nN. Kaplan-Meier and log-rank test were used to compare survival differences. Multivariate Cox proportional hazards regression model was used to analyze the influence of pN staging on overall survival (OS).
Results
According to the optimal cutoff value of nN, we classified patients into three nN categories (nN0; nNa: nN1-4; nNb: nN4-). Data from the 6th and 7th edition TNM staging indicated that survival curves were better in patients with pN2a than those with pN1b (P < 0.001). Multivariate Cox analysis also revealed that patients with pN1b and pN2a had no significant difference on OS (pN2a VS. pN1b: HR=0.926; 95%CI: 0.774-1.109; P = 0.406). Then, the modified TNM staging based on the location and number of lymph nodes was further to conduct. Survival curves of modified pN1 and pN2 were well distributed compared with the current TNM staging in both the 6th, 7th edition (P < 0.001) and the validation cohort (P = 0.049).
Conclusion
The modified TNM staging combined locational pN stage and numerical nN stage was a more accurate prognostic determinant in NSCLC patients.
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P66 - Tumor Biology and Systems Biology - Basic and Translational Science - Outcomes (ID 205)
- Event: WCLC 2020
- Type: Posters
- Track: Tumor Biology and Systems Biology - Basic and Translational Science
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P66.01 - CD44 Confers Worsened Prognosis in Lung Adenocarcinoma and is Positively Correlated With PD-L1 and Immune Cells Infiltration (ID 994)
00:00 - 00:00 | Presenting Author(s): Haiyong Wang
- Abstract
Introduction
PD-L1 is controlled by cancer cells to evade immune surveillance and was acknowledged to be a biomarker for immunotherapy. Cancer stem cells (CSCs) are a sub-population of tumor cells, which are responsible for tumor growth, metastasis and therapy resistance. However, the exact association between CSC and PD-L1 in lung adenocarcinoma (LUAD) remains to be explored. The aim of the study was to ascertain the association between CSC and PD-L1 expression in LUAD patients, with CD44 as CSC biomarker in LUAD. Moreover, the immune cells surrounding LCSC was also evaluated in the present study.
Methods
We assessed CD44 expression and its association with PD-L1 in lung adenocarcinoma (LUAD), using Tumor Immune Estimation Resource (TIMER), which was further validated in our LUAD patient cohort. The landscape of immune cells infiltration in LUAD was depicted by CIBERSORT using GEO database. The relationship between CD44 and immune cells was also analyzed. We further evaluated the prognostic role of CD44 in LUAD patients both using Kaplan-Meier plotter and validated in our LUAD patient cohort.
Results
Lower CD44 expression and its positive association with PD-L1 were found in LUAD patients. T cells CD4 memory resting cells and mast cells resting cells varied significantly between LUAD patients with CD44 high and those with CD44 low. Association could be found between CD44 expression and immune cells (B cell, CD8+ T cell, CD4+ T cell, macrophage, neutrophil, dendritic cells). CD44 arm-level deletion was associated with B cell, CD4+ T cell, neutrophil and dendritic cell infiltration. LUAD patients with higher CD44 levels had worsened overall survival (OS) and CD44 could serve as a prognostic factor in LUAD patients.
Conclusion
CD44 was associated with PD-L1 and infiltration of some immune cells, and it was proven to be a negative prognostic factor for predicting worsened OS in LUAD.
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P75 - Immunotherapy (Phase II/III Trials) - Misc. Topics (ID 248)
- Event: WCLC 2020
- Type: Posters
- Track: Immunotherapy (Phase II/III Trials)
- Presentations: 2
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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P75.02 - Non-Squamous NSCLC Patients Harbored STK11 or KEAP1 Mutation Showed Insensitivity to any Treatment Including Immunotherapy (ID 3085)
00:00 - 00:00 | Presenting Author(s): Haiyong Wang
- Abstract
Introduction
The objective of this study was mainly to analyze the prognostic effect for patients with non-squamous non-small cell lung cancer (NSCLC) harbored STK11 or KEAP1 mutation received chemotherapy and PD1/PD-L1 inhibitors.
Methods
The data from OAK and POPLAR clinical trials was firstly applied to analyze the relationship between STK11 or KEAP1 mutation and PD-L1 expression and blood tumor mutation burden (bTMB) for patients with non-squamous NSCLC; Then, the overall survival (OS) difference was compared between the patients who received atezolizumab or docetaxel harbored STK11 or KEAP1 mutation and none. Importantly, the OS difference of patients between STK11 or KEAP1 mutation and none was further confirmed using public database from the cBioPortal platform.
Results
Most STK11 (7.33% vs.1.57%) or KEAP1 (10.76% vs. 8.46%) mutation was found in non-squamous NSCLC patients comparing with squamous NSCLC. Interestingly, only 0.96% STK11 mutation and 1.92% KEAP1 mutation occurred in EGFR mutated non-squamous NSCLC patients. Compared with wild-type, higher bTMB were found in patients harbored STK11 or KEAP1 mutation (both, P < 0.001), while PD-L1 expression was higher (25% VS. 14.54%) in KEAP1 mutated patients and lower (7.89% VS. 15.9%) in STK11 mutated patients. Importantly, we found that non-squamous NSCLC patients harbored STK11 or KEAP1 mutations had worse OS no matter treated with atezolizumab monotherapy or docetaxel (all, P < 0.001). Moreover, these mutated patients could not benefit from atezolizumab compared with docetaxel (all, P > 0.05). Similarly, in further analysis of cBioPortal data, we also found that STK11 or KEAP1 mutated non-squamous NSCLC patients who received PD1/PD-L1 inhibitors or other treatment had worse survival than wild-type (all, P < 0.05).
Conclusion
Non-squamous NSCLC patients harbored STK11 or KEAP1 mutation were not sensitive to any treatment, suggesting they may be a special subtype.
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P75.09 - Analysis of Immune Microenvironment and Prognosis of NSCLC Patients Harbored SMARCA4 Mutation (ID 3086)
00:00 - 00:00 | Presenting Author(s): Haiyong Wang
- Abstract
Introduction
Ten percent of NSCLC patients harbor SMARCA4 mutations, suggesting the importance of accurate identifying these mutations. However, the role of SMARCA4 mutations on immune microenvironment is not known and it’s also unclear whether these patients could benefit from immunotherapy. Here, we aim to clarify the status of SMARCA4 mutation and its association with immune microenvironment and immunotherapy for NSCLC patients.
Methods
Using the cBioPortal database, we screened a total of 1668 NSCLC patients from MSK-IMPACT clinical sequencing cohort. The gene mutation frequency was analyzed by the cBioPortal database. In addition, using different database, we analyzed the correlation between SMARCA4 mutation and PDL1 mRNA, TMB score, neoantigens load, immunes subtye and immune cells infiltration, respectively. A total of 329 patients receiving PD1/PDL1 treatment from previous research and 1137 patients from the POPLAR and OAK trials were used to analyze survival difference.
Results
More SMARCA4 mutation was found in poorly differentiated non-small cell lung cancer (25%) compared with other.subtype (2.9% - 10.8%). In addition, SMARCA4 mutation co-occurred high KEAP1 and STK11 mutation (all P < 0.05, Q <0.05). The result showed SMARCA4 mutation was not correlation with PD-L1 mRNA (P = 0.557), but related to TMB score, neoantigens load and immune subtype (all P < 0.001). And SMARCA4 mutation was positively related to T cells follicular helper and Marcrophages M0 while negatively related to Dendritic cells testing, Mast cell testing, T cells CD4 memory testing and Monocytes (all P < 0.05). Patients with SMARCA4 mutation had worse survival compared with wild type patients (P < 0.001). And SMARCA4 mutated patients could not benefit from immunotherapy (P = 0.754). In POPLAR and OAK trials, we further made the similar result (P = 0.143) and SMARCA4 mutated patients who receiving chemotherapy had worse survival (P =0.016). In addition, we found that SMARCA4 mutated patients could benefit from immunotherapy with more than 4 months median survival extension compared with chemotherapy,
Conclusion
SMARCA4 mutated NSCLC patients had worse survival and could not benefit from chemotherapy as well as immunotherapy; however, survival of these patients receiving immunotherapy is better than that receiving chemotherapy
