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Fiona Blackhall



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    ES04 - Multimodality Management of Small Cell and Neuroendocrine Cancers (ID 7)

    • Event: WCLC 2019
    • Type: Educational Session
    • Track: Small Cell Lung Cancer/NET
    • Presentations: 1
    • Now Available
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      ES04.06 - Systemic Treatment of Large Cell Neuroendocrine Cancer (Now Available) (ID 3173)

      10:30 - 12:00  |  Presenting Author(s): Fiona Blackhall

      • Abstract
      • Presentation
      • Slides

      Abstract

      Large cell neuroendocrine cancer (LCNEC) is a rare, aggressive cancer that accounts for approximately 3% of all lung cancer. It is characterised by high-grade features (>10 mitoses/2mm2) and the presence of neuroendocrine morphology and markers (1). The diagnosis of LCNEC is distinct from both non-small cell lung cancer (NSCLC) and other pulmonary neuroendocrine tumours such as carcinoids and small cell lung cancer (SCLC). Survival is poor with only 5% of patients alive at 5 years from diagnosis regardless of stage at presentation. Conventionally treatment has mirrored that of SCLC despite limited evidence for this approach. The recommended standard of care is a combination of platinum with etoposide based on the results of one single arm phase 2 study in which there were only 29 evaluable patients (2). The median progression free survival (PFS) and overall survival (OS) rates were 5 months and 8 months respectively. Of note the observed objective response rate was 34%, lower than reported ORRs in SCLC of ~70%. Similar worse outcomes in the LCNEC population are observed for treatment with irinotecan and cisplatin (3). The explanation for this disparity is provided by emerging evidence that LCNEC can be subcategorised into two major and clinically relevant subsets according to genomic characteristics (4). A ‘SCLC-like’ genomic profile is estimated to account for about 40% of LCNEC, characterised by RB1 and TP53 that hallmark SCLC and ‘SCLC-like’ LCNEC has clinical behaviour consistent with SCLC. The other subset is ‘NSCLC-like’ with wild-type RB1 as the main distinction alongside mutations that also occur recurrently, at various frequencies, in NSCLC such as STK11, KRAS, KEAP1 and NFE2L2. The latter were hypothesised to be relatively more sensitive to chemotherapy approved for NSCLC. Consistent with this, in a carefully conducted retrospective analysis patients with NSCLC-like LCNEC (RB1 wild type) who received platinum with gemcitabine or a taxane had a median OS of 9.6 months whereas those who received platinum and etoposide had a significantly shorter median OS of 5.8 months (p=0.026) (5). These results question the current standard of care for LCNEC and highlight the need for prospective examination of molecular subtyping to direct treatment decision making. The molecular heterogeneity underpinning LCNEC may also have implications for selection of immune checkpoint inhibitors (6) and other precision medicines targeting actionable mutations (7). The advent of specific KRAS inhibitors that appear promising in early phase development (8) generates further impetus to redesign our therapeutic algorithms for LCNEC according to genomic context if we are to improve outcomes for patients with this orphan disease.

      References

      1. Travis WD, Brambilla E, Nicholson AG, Yatabe Y, Austin JHM, Beasley MB, et al. The 2015 World Health Organization Classification of Lung Tumors. Journal of Thoracic Oncology.10(9):1243-60.

      2. Multicentre phase II study of cisplatin-etoposide chemotherapy for advanced large-cell neuroendocrine lung carcinoma: the GFPC 0302 study. Le Treut J et al. Ann Oncol. 2013: 24(6):1548-52.

      3. Combination chemotherapy with irinotecan and cisplatin for large-cell neuroendocrine carcinoma of the lung: a multicentre phase II study. Niho et al. J Thoracic Oncol 2013: 8:980-4

      4. Next-Generation Sequencing of Pulmonary Large Cell Neuroendocrine Carcinoma Reveals Small Cell Carcinoma–like and Non–Small Cell Carcinoma–like Subsets. Rekhtman N et al. Clinical Cancer Research. 2016;22(14):3618.

      5. Molecular Subtypes of Pulmonary Large-cell Neuroendocrine Carcinoma Predict Chemotherapy Treatment Outcome. Derks JL et al. Clinical Cancer Research. 2018;24(1):33.

      6. Genomic Alterations (GA) and Tumor Mutational Burden (TMB) in Large Cell Neuroendocrine Carcinoma of Lung (L-LCNEC) as Compared to Small Cell Lung Carcinoma (SCLC) as Assessed Via Comprehensive Genomic Profiling (CGP). Chae et al. J Clin Oncol 2017; 35:15 suppl, 851

      7. Comparison of genomic landscapes of large cell neuroendocrine carcinoma, small cell lung carcinoma, and large cell carcinoma. Zhou Z et al. Thorac Cancer 2019 10(4):839-847

      8. Direct Ras G12C Inhibitors : Crossing the Rubicon. Lindsay C and Blackhall F. BJC. 2019 In press

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    MA19 - Looking at PROs in Greater Detail - What Patients Actually Want and Expect (ID 147)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Treatment in the Real World - Support, Survivorship, Systems Research
    • Presentations: 1
    • Now Available
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      MA19.09 - Assessing Clinical Frailty in Advanced Lung Cancer Patients - An Opportunity to Improve Patient Outcomes? (Now Available) (ID 2363)

      11:30 - 13:00  |  Author(s): Fiona Blackhall

      • Abstract
      • Presentation
      • Slides

      Background

      The median age of non-small cell lung cancer (NSCLC) diagnosis in England is 73 years. At that age, 40% of the general population has some degree of clinical frailty which may impact survival, quality of life, anti-cancer treatment tolerability and access to clinical trials. However, clinical frailty is often not addressed or managed at the time of anti-cancer treatments. This project was designed to integrate frailty assessments and build frailty pathways within an advanced cancer care setting in order to better support patients and improve outcomes.

      Method

      This quality improvement project that used Plan-Do-Study-Act (PDSA) methodology. Phase one of the project focused on establishing a multidisciplinary team to integrate a frailty screening tool, the Rockwood Clinical Frailty Scale (CFS), into standard clinical practice. The primary aim was to implement and screen ≥80% of all new lung cancer patients at a high-volume tertiary cancer centre. The secondary aim was to explore the correlation of CFS with age, performance status (PS), treatment selection and systemic anti-cancer treatment (SACT) tolerability. Specialised training was provided to the clinical team and the CFS was integrated from 26/11/2018 on an electronic form routinely completed by clinicians. A digital dashboard was set-up to monitor real-time data and the frail group was defined as CFS score >3. Data cut-off for this analysis was 29-03-2019.

      Result

      335 lung cancer patients were screened using CSF by a team of 20 clinicians with a compliance rate of 89%. There was a strong correlation between PS and CFS (r= 0.77, p<0.01). The distribution of both CFS and PS correlated with ageing (r= 0.2 and r= 0.17, respectively; p<0.01). Patients ≥70 years were more likely to be frail (56% vs 40%; OR 1.4, 95%CI 1.2-1.7; p<0.01). Frailty reduced the likelihood of receiving any anti-cancer treatment by 20%. Amongst those who started SACT, patients classed as frail were less likely to go beyond the first cycle of treatment (64% vs 91%; OR 0.7, 95%CI 0.5-0.9; p<0.01).

      Conclusion

      CFS screening is feasible within a busy clinical practice when incorporated as a digital tool. CFS helps to identify patients who may potentially benefit from specialised frailty assessment and management. This could ultimately be used to better inform on treatment selection, and support requirements during treatment, to improve outcomes for patients in the future.

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    MA25 - Precision Medicine in Advanced NSCLC (ID 352)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Advanced NSCLC
    • Presentations: 1
    • Now Available
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      MA25.08 - Characterisation of Tumor Aetiology Using Mutational Signatures from the Non-Small Cell Lung Cancer Genome (Now Available) (ID 2667)

      14:30 - 16:00  |  Author(s): Fiona Blackhall

      • Abstract
      • Presentation
      • Slides

      Background

      Somatic genome and exome analyses in cancer are currently dominated by a search for actionable mutations that inform new treatments for stage IV patients. Tumour mutational signatures, originally described by the Sanger centre, offer the potential to understand cancer cure and prevention strategies by using the genome/exome to define aetiological contributions to cancer from both environmental and endogenous sources.

      Method

      132 NSCLC samples were resected from 131 Greater Manchester patients and submitted to the UK 100,000 Genomes Project (Genomics England). A 5×5×5 mm fresh tumour sample was taken from the surgical specimen and stored at -80°C before undergoing genomic testing. To determine the neoplastic cell count, an additional tumour biopsy was taken for routine histological assessment. Germline DNA for comparable whole genome analysis was extracted from peripheral blood lymphocytes from a paired whole blood sample.Whole genome sequencing (WGS) was performed on tumor specimens and matched blood samples. Through the 100,000 Genomes Project pipeline, coverage was calculated from high-quality, non-overlapping bases present on well-mapped reads, as defined by SAMtools v1.1. Whole genome sequencing analysis was undertaken with the Illumina North Star pipeline v2.6.53.23. Data were then mined for tumour mutational burden (TMB) and mutational signature profiles. Signatures were extracted if they accounted for >5% of the mutations per sample. Clinical characteristics including tumor size, nodal status and stage were documented. Mann-Whitney and Fisher’s exact tests were used for statistical comparisons.

      Result

      Signature 8 (unknown aetiology) was the most prevalent mutational process overall (122/132 samples, 92.4%), while smoking signature 4 was the main mutational process in 86/131 (65.6%) of NSCLC cases. SIgnature 4 contributed as a principal or secondary mutational process to a total of 105/131 (80.2%) cancers; 104/105 (99%) of these patients were annotated as smokers or ex-smokers. Signature 5 (unknown aetiology) was the second most common driving signature (24/131, 18.3% cancers), contributing to an additional 19 cancers as a secondary mutational process (43/131, 32.8% of cancers overall). Median number of signatures contributing to signature 4 NSCLC was four, whilst non-smoking mediated NSCLC had contributions from a median of 5.5 mutational signatures (range 2-8). A median of four signatures contributed to both adenocarcinomas and squamous cancers, with 61/88 (69.3%) adenocarcinomas and 25/41 (61%) squamous cancers associated with signature 4 as their main mutational process. More results will follow on duration of signature 4 persistence following discontinuation of smoking, as well as prevalence of each signature according to common molecular subtypes of NSCLC.

      Conclusion

      Tumor mutational signatures have the potential to inform cancer prevention by offering a new level of genetic detail that reflects environmental and endogenous carcinogenesis. As expected, signature 4 offers the main contribution to NSCLC although a number of other aetiological factors are involved in its carcinogenesis. In particular, signatures 5 and 8, both currently of unknown aetiology, significantly contribute to the NSCLC genome. Along with that reported by the Sanger centre, this work lays the foundations for characterisation and identification of new carcinogens.

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    P1.04 - Immuno-oncology (ID 164)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Immuno-oncology
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.04-44 - Radiomics for Predicting Response to First-Line Anti-PD1 Therapy in Advanced NSCLC (Now Available) (ID 2172)

      09:45 - 18:00  |  Author(s): Fiona Blackhall

      • Abstract
      • Slides

      Background

      Radiomics is the high-throughput extraction of quantitative imaging features from medical images that can reflect underlying tumour pathophysiology. Imaging biomarkers have the potential to improve disease characterisation and predict patient outcomes. In this study, the utility of radiomic features to predict response and survival to first-line immune check-point inhibition with pembrolizumab in advanced non-small cell lung cancer (NSCLC) was explored.

      Method

      Patients with Stage IIIB/IV NSCLC treated with first-line pembrolizumab and PD-L1 ≥50% were retrospectively identified and stratified by Best Overall Response (BOR) by RECIST 1.1. Patients with the primary tumour in situ and a contrast-enhanced CT thorax/abdomen (minimum 5mm CT slice thickness) at baseline were included. The single largest thoracic lesion was segmented in the diagnostic image using the Pinnacle radiotherapy treatment planning system. All tumour delineations were supervised by a highly experienced certified senior radiologist. Lesions <1cm, inflammatory and indeterminate lesions were excluded from delineation. A total of 47 radiomic features including shape, first-order and texture features were extracted from the segmented tumour using PyRadiomics. No pre-processing of the images was performed. Highly correlated features (r>0.85) were removed from further analysis. Least Absolute Shrinkage and Selection Operator (LASSO) feature selection was performed to find informative features that could predict either best overall response or overall survival. Univariate logistic regression and cox proportional hazard models were then used for an initial assessment of the potential of these features in predicting response and survival respectively.

      Result

      Sixteen patients with evaluable best overall response (partial response n=9, progressive disease n=7) were selected for the initial discovery-cohort. Mean age was 68 years with 63% adenocarcinoma histology. From the 47 features extracted, 32 were highly correlated to each other and were removed from further analysis. For predicting best overall response, LASSO selected 5 features with univariate logistic regression suggesting that tumour surface area to volume ratio might be informative (p=0.057, AUC of 0.83 (95% CI 0.61-1.0)). With respect to overall survival, LASSO selected 3 features with univariate cox regression suggesting the first-order feature skewness might be predictive (HR = 0.27, 95% CI 0.08-0.88, p=0.03). When split on the median skewness value the Kaplan-Meier plot showed a significant survival difference between high and low risk patients (p=0.007).

      Conclusion

      Radiomic features extracted from baseline contrast-enhanced CT scans may have the potential to predict response and survival in patients treated with first-line pembrolizumab in advanced NSCLC. We emphasize the exploratory nature of these results given the very limited number of patients in the study. We are expanding this discovery cohort to further investigate and validate these results. Updated results will be presented at the meeting.

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    P2.09 - Pathology (ID 174)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Pathology
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.09-23 - PD-L1 Expression of Paired Primary Resected Non Small Cell Carcinoma and Metastatic Lymph Node Fine Needle Aspirates (Now Available) (ID 2640)

      10:15 - 18:15  |  Author(s): Fiona Blackhall

      • Abstract
      • Slides

      Background

      Small biopsy or cytology samples may present with a different level of PD-L1 expression compared to resected samples (which usually entail scoring of a much greater number of cells) resulting in relatively increased or reduced tumour proportion scores (TPSs). Many PD-L1 results are based on cytology fine needle lymph node aspirates (FNLNAs), encompassing analysis of metastatic disease and the substitution of cytology for histology samples. We compared the PD-L1 TPS of metastatic FNLNAs with that of resected non small cell carcinoma.

      Method

      The pathology archive at Wythenshawe Hospital was searched for cases with adequate material over a period spanning 2010-2016. The Ventana SP263 PD-L1 clone was used to stain blocks select from 50 resected NSCCs and matched FNLNA cell blocks from each individual, along with a fresh H&E and negative PD-L1 control section.

      Result

      Four of the cell block sections were inadequate for TPS assessment. The remaining 46 cases comprised 21 adenocarcinomas, 3 large cell carcinomas, 1 large cell neuroendocrine carcinoma, 1 atypical carcinoid tumour, and 20 squamous carcinomas. 34 cell block PD-L1 TPSs (68%) were in broad agreement with the corresponding resection block TPS, based on cut-off levels of 1% and 50%. Of the 12 (32%) cases in which differences occurred, 6 (50%) reflected an increase in TPS from resection to FNA, while 6 reflected a decrease causing a change in therapeutic cut-off. Nine of the FNLNAs were sampled after the resection, favouring the presence of recurrent disease.

      TABLE 1. PD-L1 expression of resections versus FNLNAs across TPS categories

      Resection Tumour Proportion Scores n, (%)

      FNLNA Tumour Proportion Scores n, (%)

      0 / <1%

      1 - 49%

      ≥ 50%

      p

      0 / <1% 1 - 49% ≥ 50% p

      Total n = 46

      12 (26)

      15 (33)

      19 (41)

      16 (35)

      7 (15)

      23 (50)

      0.14

      Median age at diagnosis (yrs)

      63 64 64 62 69 64

      Adenocarcinoma

      Squamous ca.

      Othera

      2 (4)

      7 (15)

      3 (7)

      8 (20)

      6 (11)

      1 (2)

      10 (22)

      8 (17)

      1 (2)

      0.132

      2 (4)

      10 (22)

      4 (9)

      5 (11)

      2 (4)

      0 (0)

      13 (28)

      9 (20)

      1 (2)

      0.035

      Discrepant cases n = 12

      1 (8)

      9 (75)

      2 (17)

      4 (33)

      2 (17)

      6 (50)

      a Includes large cell carcinoma, large cell neuroendocrine carcinoma, atypical carcinoid

      Conclusion

      The majority of metastatic TPS FNLNAs are in broad agreement with a primary resected carcinoma TPS. FNLNAs tended to score less in the 1-49% category, possibly due to limits of cellularity. In addition to heterogeneity of expression, sampling of recurrent rather than residual disease may contribute to discrepancies.

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