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Zhaolin Xu
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MA09 - Lung Cancer Surgical and Molecular Pathology (ID 908)
- Event: WCLC 2018
- Type: Mini Oral Abstract Session
- Track: Pathology
- Presentations: 1
- Moderators:
- Coordinates: 9/24/2018, 15:15 - 16:45, Room 202 BD
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MA09.10 - Molecular Profiling and PD-L1 Status in 900 Cases of Surgically Resected Non-Small Cell Lung Cancer with Clinical and Pathological Correlation (ID 11188)
16:20 - 16:25 | Presenting Author(s): Zhaolin Xu
- Abstract
- Presentation
Background
Precision medicine provides efficient treatment options for lung cancer patients as it targets the individual tumor’s genetic makeup. Recent development of immune therapy based on immune checkpoint inhibitor also provides hope for patients. Currently lung cancer mutational data available in the literature are mainly from advanced stage non-small cell lung cancer. There is insufficient information from early stage lung cancer patients. PD-L1 status in relation to clinical and pathological characteristics is also unclear. This study tried to address these issues from 900 cases of surgically resected lung cancer.
a9ded1e5ce5d75814730bb4caaf49419 Method
Multiplexed molecular profiling in 900 surgically resected lung cancer specimens. A panel of gene including EGFR, KRAS, BRAF, PIK3CA, HER2 and ALK was tested. PD-L1 was also evaluated by immunohistochemistry using pharmDx22C3. Tumor proportional score (TPS) in a 10% increment was measured. Mutational status and PD-L1 TPS in each cancer subtype in relation to cancer pathological characteristics were investigated. Correlations between gene mutation, PD-L1 status and cancer staging were performed. Gene mutation and PD-L1 status with patients’ demographic information such as gender, age, smoking history, as well as survival data after surgery were also analysed.
4c3880bb027f159e801041b1021e88e8 Result
This cohort includes adenocarcinoma (65%), squamous cell carcinoma (24%), large cell carcinoma (6%), other subtypes (5%). Stage I accounts for 56%, stage II, 26%, stage III, 16%, stage IV, <2% with a mean age of 66 years. In adenocarcinoma, KRAS accounts for 36%, EGFR 10%, BRAF 1%, PIK3CA 1%, ALK 0.2%, no mutations 52%. Only 5% squamous cells carcinoma showed mutations.
PD-L1 TPS <1% accounts for (37%), TPS 1-9% (18%), TPS 10-19% (7%), TPS 20-29% (5%), TPS 30-39% (5%), TPS 40-49% (1%), TPS 50-59% (5%), TPS 60-69% (4%), TPS 70-79% (4%), TPS 80-89% (5%), TPS 90-99% (7%) and unsuccessful (2%). EGFR mutations were significantly associated with female (p<0.001) and never smokers (p<0.001), with well differentiated adenocarcinoma (p<0.001), and with absence of vascular invasion (p<0.01). KRAS mutations were more prevalent in younger age group (p=0.003). Poorly differentiated cancer histology was associated with absence of KRAS or EGFR mutations. There was no significant association between PD-L1 expression and age, sex, pathological stage and smoking status. PD-L1 expression was significantly associated with vascular invasion (p=0.035). EGFR mutations were significant associated with absence of PD-L1 expression (p=0.02), but no association between KRAS mutations and PD-L1 expression (p=0.10).
8eea62084ca7e541d918e823422bd82e Conclusion
This study provides comprehensive information enhancing our knowledge in depth about driver gene mutations and immune checkpoint PD-L1 status in non-small cell lung cancer patients.
6f8b794f3246b0c1e1780bb4d4d5dc53Only 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, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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OA08 - Mesothelioma: Immunotherapy and microRNA for Diagnosis and Treatment (ID 907)
- Event: WCLC 2018
- Type: Oral Abstract Session
- Track: Mesothelioma
- Presentations: 1
- Moderators:
- Coordinates: 9/24/2018, 15:15 - 16:45, Room 201 BD
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OA08.07 - In Silico Discovery of Unannotated miRNAs in Malignant Pleural Mesothelioma Reveals Novel Tissue-of-Origin Markers (ID 14155)
16:20 - 16:30 | Author(s): Zhaolin Xu
- Abstract
- Presentation
Background
Malignant pleural mesothelioma (MPM) is an aggressive disease. One of the major clinical challenges associated with MPM is the lack of biomarkers capable of distinguishing primary MPM from cancers that have metastasized to the pleura. The current gold standard consists of a panel of positive and negative protein markers to confirm tissue-of-origin; however, many cases remain undistinguishable from other thoracic cancers. Recent studies have suggested that the human genome encodes more microRNAs (miRNAs) than currently annotated. These undescribed sequences have been shown to display enhanced tissue and lineage specificity. Therefore, we hypothesize that MPM tumors express a specific set of previously unannotated miRNA sequences with tissue-specific expression capable of distinguishing MPM from other thoracic diseases.
a9ded1e5ce5d75814730bb4caaf49419 Method
Novel miRNA candidates were detected from small RNA-sequencing data generated by The Cancer Genome Atlas (TCGA) (n=87 MPM) using the miRDeep2 algorithm, a well-established novel-miRNA prediction algorithm. The possible biological roles of these miRNA candidates were investigated by performing a genome-wide 3’UTR target prediction analysis. Additionally, their tissue-specificity was assessed using expression profiles of 1,093 lung tumors from four independent cohorts of adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Finally, we developed a miRNA-based classifier model using the weighted voting class prediction method to distinguish MPM from other thoracic cancers.
4c3880bb027f159e801041b1021e88e8 Result
Our initial analysis revealed 424 miRNA candidates, which were subsequently filtered by RNA structure, abundance of sequencing reads, and genomic location, resulting in 154 previously unannotated miRNA sequences. Interestingly, the novel miRNAs were predicted to target protein-coding genes involved in MPM biology, including the Ataxia Telangiectasia Mutated (ATM) gene, a tumour-supressor gene frequently mutated in MPM. Likewise BRCA1 Associated Protein 1 (BAP1), involved in the DNA damage response pathway, was also a predicted target. Principal component analyses revealed that novel-miRNA expression was able to distinguish MPM from LUAD and LUSC. Furthermore, our miRNA-based classifier model revealed 10 novel miRNAs capable of successfully identifying 86 out of the 87 MPM cases (98.80%) and 100% of LUAD cases (true positive rate = 98.85%, false positive rate = 1.150%).
8eea62084ca7e541d918e823422bd82e Conclusion
Here, we provide evidence for the presence of 154 previously unannotated miRNA species relevant to MPM. These miRNAs not only significantly expand the miRNA repertoire but also unveil specific roles in MPM biology. Most importantly, the strikingly high sensitivity and specificity of the novel miRNA-based classifier in distinguishing MPM from LUAD illustrates the potential of using these novel miRNAs to supplement current clinical markers to define MPM.
6f8b794f3246b0c1e1780bb4d4d5dc53Only 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, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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P3.03 - Biology (Not CME Accredited Session) (ID 969)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/26/2018, 12:00 - 13:30, Exhibit Hall
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P3.03-02 - Single-Cell RNA-Seq in Human Lung Cancer (ID 13405)
12:00 - 13:30 | Author(s): Zhaolin Xu
- Abstract
Background
Lung cancer has the highest mortality rate amongst cancers primarily due to delay of diagnosis. Until recently, the focus on genomic and transcriptomic characterization of lung cancers has guided to the diagnosis and treatments of the cancers. Although RNA sequencing (RNA-seq) has been used for transcriptome profiling in cancer research, few studies have employed single cell (sc) RNA-seq approaches to investigation of the heterogeneity among individual cells directly isolated from resected surgical human lung cancer tissues. The aim of our work is to identify new biomarkers indicating early stage versus late stage of lung cancers. As an initiative step, the current study presents a profile of differentially expressed genes (DEG) of single cells of lung cancer tissues collected from diverse lung cancer patients.
a9ded1e5ce5d75814730bb4caaf49419 Method
Tumours resected from lung cancer patients were prepared for scRNA-seq. Microfluidic system, C1 (Fluidigm), was used to capture individual cells, and full-length cDNAs (FL-cDNA) were synthesized in the system. Next-generation sequencing (Illumina) of FL-cDNA libraries generated sequence reads from transcriptomes of single and bulk cells, respectively. Following read mapping, DEGs were selected by >2x fold-change difference in normalized expression values. qPCR was employed to validate transcriptional changes in selected DEGs comparing expression values resulted from scRNA-seq and bulk RNA-seq. Both gene set enrichment and signaling pathway analyses were used to identify mechanism of action for validated DEG-encoding molecules.
4c3880bb027f159e801041b1021e88e8 Result
Raw scRNA-seq datasets were processed for read mapping. More than 1 million processed reads per single-cell FL-cDNA library were used for DEG selection. We examined standard deviation of normalized expression value per selected DEG to characterize transcriptomic features of individual tumour cells. We identified a minimum of a dozen DEGs showing certain fold-change differences in each stage of lung cancers. Selected DEGs were validated by qPCR whereby unique patterns of gene expression at specific stages were confirmed.
8eea62084ca7e541d918e823422bd82e Conclusion
The heterogeneity of lung cancers coupled with late stage diagnosis contributes to poor outcomes. The advent of scRNA-seq allows for the identification of differential gene expression and stage-specific markers that can be used to improve our understanding of highly complex intratumour heterogeneity in lung cancers. In the future, our discoveries will lead to the development of targeted therapies based on validated DEGs, ultimately allowing for early diagnosis, treatment and improved lung cancer survivorship.
PAM is supported by CCSRI-i2I and DMRF.
6f8b794f3246b0c1e1780bb4d4d5dc53
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P3.09 - Pathology (Not CME Accredited Session) (ID 975)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/26/2018, 12:00 - 13:30, Exhibit Hall
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P3.09-11 - Genomic Organization at Large Scales (GOALS) within Nuclei and Cell Sociology for Predicting Lung Cancer Outcomes (ID 14160)
12:00 - 13:30 | Author(s): Zhaolin Xu
- Abstract
Background
Accurate prediction of the biological aggressiveness of lung cancers in patients from limited material could have utility with respect to patient treatment planning. We examined the hypothesis that the quantification of large scale DNA organization or GOALS within the nucleus combined with tumour microenvironment as quantified by cell sociology (which cells types are adjacent which cell types) could predict patient outcomes.
a9ded1e5ce5d75814730bb4caaf49419 Method
Tissue (TMA cores) from patients with poor outcomes (lung cancer mortality within 24 months) and good outcomes (5+ year survivors) was stained using a stochiometric DNA stain (Feulgen-Thionin). High resolution brightfield imaging of 29 cores was performed using multiple wavelengths and spectral unmixing used to retrieve the DNA concentration at every pixel. In house software was used to automatically segment all the nuclei within each core, calculate 100+ features for each nucleus and classify each nucleus as epithelial, stromal or immune in origin. Further each nucleus was scored as coming from a patient with poor or good outcome.
For each TMA core the percentage of these cell categories was tabulated as well as cell-cell association frequencies (for example the frequently an epithelial cell predicted to have come from a patient with good outcome was found next to a stromal cell predicted to come from a patient with poor outcome). Cell percentages and cell-cell interaction frequencies were used to predict patient outcome.
4c3880bb027f159e801041b1021e88e8 Result
8eea62084ca7e541d918e823422bd82e Conclusion
Many of the individually calculated features had a statistically significant association with patient outcome. Four+ features could predict outcome with an 79% accuracy, 15+ different pairs of features could predict patient outcome with greater than 85% accuracy. Epithelial- stromal cell interactions and stromal cell – immune cell interactions were particularly predictive of outcome suggesting that microenvironment cell - tumour cell interactions predict future biological activity.
This pilot study suggests that GOALS and cell sociology could predict patient outcomes.
6f8b794f3246b0c1e1780bb4d4d5dc53
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P3.13 - Targeted Therapy (Not CME Accredited Session) (ID 979)
- Event: WCLC 2018
- Type: Poster Viewing in the Exhibit Hall
- Track:
- Presentations: 1
- Moderators:
- Coordinates: 9/26/2018, 12:00 - 13:30, Exhibit Hall
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P3.13-31 - Creating a Precision Medicine Pipeline for Lung Cancers. (ID 14006)
12:00 - 13:30 | Author(s): Zhaolin Xu
- Abstract
Background
The vision of High Mortality Cancer Precision Medicine Pipeline (HMCPMP) is to improve high mortality cancer outcomes. Our mission of HMCPMP is to establish precision medicine pipelines for high mortality cancers that start with the patient and ends with precise treatments for the patient based on their lung cancer’s unique molecular profile. HMCPMP leverages expertise areas of i) single-cell gene-discovery that allows for the identification of new barcodes and therefore new targets, ii) animal models that recapitulate human cancers, and patient-derived xenographs that allow for pre-clinical trials in mouse models to test novel drugs and drug development, iii) immunology and cancer stem cell biology to explore the role the immune system and stem cell niche impact tumourigenesis, iv) single-cell fluidics/3D organ systems that allow for understanding the heterogeneity of cancers and vi) data mining that allows for better treatment choices and the discovery of new treatment options based on their lung cancer’s barcodes.
a9ded1e5ce5d75814730bb4caaf49419 Method
We have created a patient-centered precision medicine pipeline that moves resected lung cancers from the surgical suite to banking, through to single cell molecular diagnostics to validation (Figure 1).
4c3880bb027f159e801041b1021e88e8 Result
Single-cell genomic profiling of resected lung cancers were prepared using a microfluidics platform Fluidigm C1 followed by transcriptome sequencing per single cell. We identified differentially expressed genes (DEGs) for stage, sex, and smoking status, followed by validation by quantitative PCR. We are currently pursuing new barcodes that differentially distinguish between the stratified subgroups of patients.
8eea62084ca7e541d918e823422bd82e Conclusion
The significance of HMCPMP research is improved health, survivorship, and quality of life for people living with lung cancer. Although the economics of lung cancer are important and likely drivers of federal, provincial and regional research initiative, HMCPMP considers the human when faced with the diagnosis of lung cancer.
PAM is funded by the Dalhousie Medical Research Foundation and the Canadian Cancer Society
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