Virtual Library

Start Your Search

Wei Zhang



Author of

  • +

    JCSE01 - Perspectives for Lung Cancer Early Detection (ID 779)

    • Event: WCLC 2018
    • Type: Joint IASLC/CSCO/CAALC Session
    • Track: Screening and Early Detection
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/23/2018, 07:30 - 11:15, Room 202 BD
    • +

      JCSE01.19 - ALTER-0303 Study: Tumor Mutation Index (TMI) For Clinical Response to Anlotinib in Advanced NSCLC Patients at 3rd Line (ID 14708)

      11:15 - 11:15  |  Author(s): Wei Zhang

      • Abstract
      • Slides

      Background

      Anlotinib is an effective multi-targeted receptor tyrosin kinase inhibitor (TKI) for refractory advanced Non-Small Cell Lung Cancer (NSCLC) therapy at 3rd line. ALTER-0303 clinical trial has been revealed that Anlotinib significantly prolongs progression free survival (PFS; Anlotinib: 5.37 months vs Placebo: 1.40 months) and overall survival (OS; Anlotinib: 9.63 months vs Placebo: 6.30 months) with the objective response rate (ORR) of 9.18% and the disease control rate (DCR) of 80.95%. Here, we sought to understand the gene mutation determinants for clinical response to Anlotinib via next generation sequencing (NGS) upon cell-free DNA (cfDNA) and circulating tumor DNA (ctDNA) at baseline.

      Totally 437 advanced NSCLC patients enrolled in ALTER-0303 study, and 294 patients received Anlotinib therapy. Of the 294 patients, 80 patients were analyzed in the present study. Capture-based targeted ultradeep sequencing was performed to obtain germline and somatic mutations in cfDNA and ctDNA. Response analyses upon discovery cohort (n = 62) and validation cohort (n = 80) were performed by use of germline and somatic (G+S) mutation burden, somatic mutation burden, nonsynonymous mutation burden, and unfavorable mutation score (UMS), respectively. Based on the above independent biomarkers and their subtype factors, tumor mutation index (TMI) was developed, and then used for response analysis.

      Our data indicated that the patients harbouring less mutations are better response to Anlotinib therapy (G+S muatation burden, cutoff = 4000, Median PFS: 210 days vs 127 days, p = 0.0056; somatic mutation burden, cutoff = 800, Median PFS: 210 days vs 130 days; p = 0.0052; nonsynonymous mutation burden, cutoff = 50, Median PFS: 209 days vs 130 days; p = 0.0155; UMS, cutoff = 1, Median PFS: 210 days vs 131 days; p = 0.0016). TMI is an effective biomarker for Anlotinib responsive stratification (Median PFS: 210 days vs 126 days; p= 0.0008; AUC = 0.76, 95% CI: 0.62 to 0.89) upon discovery cohort and validation cohort (Median PFS: 210 days vs 127 days; p = 0.0006). Lastly, integrative analysis of TMI and IDH1 mutation suggested a more promising result for Anlotinib responsive stratification upon validation cohort (Median PFS: 244 days vs 87 days; p < 0.0001; AUC = 0.90, 95% CI: 0.82 to 0.97).This study provide a biomarker of TMI to stratify Anlotinib underlying responders, that may improve clinical outcome for Anlotinib therapy on refractory advanced NSCLC patients at 3rd line. Clinical trial information: NCT02388919.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.

  • +

    P1.03 - Biology (Not CME Accredited Session) (ID 935)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 2
    • Now Available
    • Moderators:
    • Coordinates: 9/24/2018, 16:45 - 18:00, Exhibit Hall
    • +

      P1.03-05 - Transcriptome Landscape of Lung Adenocarcinoma Patients Revealed Distinct Trajectory Patterns (Now Available) (ID 12025)

      16:45 - 18:00  |  Author(s): Wei Zhang

      • Abstract
      • Slides

      Background

      The hallmarks of cancer was proposed to elucidate the common trajectory of tumors of different tissues of origin and genetic makeups, which were expected to attributed to disruption of regulatory pathways conferring survival and growth advantages to tumor tissues. However, the specific biological processes involved in each milestones in the trajectory of development of lung adenocarcinoma, particularly regarding tumor stages, remain elusive. The datasets of The Cancer Genome Atlas (TCGA) project lend potential for discovering the distinctive expressional patterns of differentiated subpopulations, and exploring the dynamic evolution of biological activities within tumor cells.

      Method

      RNA sequencing level 3 data of 56 pairs of tissue and adjacent normal samples were obtained from TCGA. Differential expression analysis was conducted using ‘edgeR’ package across the each tumor stage. Differentially expressed genes were derived with fold change>=4 and FDR <= 0.01, followed by KEGG pathway analysis. Odd ratios (ORs) were extracted to indicate the degrees of dysregulation of each pathway.

      Result

      After removing non-cancer associated pathways from the 77 pathways identified as dysregulated in those samples, we arrived at 35 pathways. In “Cell cycle” and “Pathways in cancer”, ORs display positive correlation with tumor stages, and the Stage IV showed appreciably higher OR than other stages. Noteworthily, Stage IV has very high Ors in “PPAR signaling pathway”, “Renin-angiotensin system” and “p53 signaling pathway”, which represents canonical pathways implicated in cancer pathologies.

      figure.jpg

      Conclusion

      We identified pathways that display correlation with tumor stages, although some deviations are expected to stem from differences in treatment, complicated disease, and health conditions, etc. These results display considerable linear correlation between the degree of dysregulation of cancer pathways, which promise applying RNA sequencing in characterizing the bona fide cell fate of tumor tissues.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.

    • +

      P1.03-30 - The Number of Mutated Repair Genes as Predictor for Tumor Mutation Burden of Lung Adenocarcinoma (Now Available) (ID 12027)

      16:45 - 18:00  |  Author(s): Wei Zhang

      • Abstract
      • Slides

      Background

      Disruption of repair gene products will result in higher risk of mutation events and genetic instability. Despite some repair genes such as BRCA1 and FANCA being intensively reported in breast cancer, ovarian cancer, and the predisposition to cancers, the effects of protein dysfunction of repair genes on mutation events have not been quantified. The established repair pathways are responsible for different mutation events and may account for respective mutation patterns. Therefore, we conducted an in-depth investigation of effect of individual repair pathways or individual repair genes on tumor mutation burden (TMB).

      Method

      We obtained level 4 variant datasets from The Cancer Genome Atlas (TCGA) which comprises of 568 samples. The TMB of each individual was calculated and the population was divided into subgroups as per the status of harboring mutations in repair genes as well as the specific repair pathways.

      Result

      In the 568 lung adenocarcinoma patients, 434 patients have somatic mutations in any of the 112 DNA repair genes. The individuals harboring mutations in repair genes have significantly higher TMB (Mean=3.019, S.E.=0.206) than those do not (Mean=11.085, S.E.=0.493), and we derived a 3.81-fold increase in TMB for mutations occuring in an additional repair gene. Those that harbor mutations in TP53 account for 63% of the population, and ATM and PRKDC account for 11% and 10, respectively.

      figure.jpg

      Conclusion

      We identified most highly mutated repair genes and quantified the increase in risk for each additional mutated repair gene. Although the TMB of individuals with mutations in specific repair gene or pathway show no significant difference, a larger dataset that comprises adequate number of samples within each explanatory variables such as incidence of cell division, tumor stages to be taken into model, can be expected to derive a more robust predictor.

      Only Active Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login or select "Add to Cart" and proceed to checkout.

  • +

    P2.15 - Treatment in the Real World - Support, Survivorship, Systems Research (Not CME Accredited Session) (ID 964)

    • Event: WCLC 2018
    • Type: Poster Viewing in the Exhibit Hall
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/25/2018, 16:45 - 18:00, Exhibit Hall
    • +

      P2.15-22 - Optimal Glycemic Control Improves Prognosis for Lung Cancer Patients with Diabetes Mellitus (ID 14008)

      16:45 - 18:00  |  Author(s): Wei Zhang

      • Abstract

      Background

      Diabetes mellitus (DM) is a common comorbidity in patients with lung cancer (LC). This study aimed to evaluate the prognostic value of DM comorbidity for LC patients with DM and to assess whether an optimal glycemic control improves survival.

      Method

      A total of 4390 patients diagnosed with LC between 2012 and 2013 at Shanghai Chest Hospital were retrospectively reviewed, 491 patients with DM and 3899 without DM. The relationship between hemoglobin A1c (HbA1c) level and the overal survival (OS) was plotted by a smooth curve. LC patients with DM were subdivided into the well-controlled group (HbA1c < 7%, n=438) and uncontrolled group (HbA1c ≥ 7%, n=53). OS differences among patients without DM, with well-controlled DM, and uncontrolled DM were evaluated by multivariate Cox regression analysis with adjustment for stage, sex, age, histology, smoking history and EGFR mutation status. The survival benefit of well-controlled DM was compared across subgroups.

      Result

      The median follow-up of the entire cohort was 35.8 months. DM patients (11.2%) had a significantly worse OS than nondiabetic patients [median (95% CI): 47.5 (39.0-56.1) vs. 73.6 (54.8-92.4) months, P<0.001]. The risk of mortality increased along with the elevation of HbA1c level. Uncontrolled DM patients tended to be male, elder, non-adenocarcinoma, with smoking history, wide-type EGFR mutations and advanced stage. Well-controlled DM patients had a worse OS [HR (95% CI): 2.3 (1.9-2.7), P<0.001] compared to nondiabetic patients without adjustment but a similar OS with adjustment for stage, sex, age, histology, smoking history and EGFR mutation status [HR (95% CI): 0.9 (0.8-1.1), P=0.185]. Benefit of well-controlled DM was more obviously seen in patients with advanced stage (III-IV) [HR (95% CI): 0.8 (0.6-1.1), P=0.130] or EGFR mutations [HR (95% CI): 1.2 (0.9-1.5), P=0.262].

      Conclusion

      Elevated glycemic status negatively affected OS for patients with LC. LC patients with DM is recommended to have a glycemic control (HbA1c < 7%) especially for those with advanced stage and EGFR mutations.