Displaying One Session

Salamanca Auditorium (Hall 3) Poster Discussion session
Date
29.09.2019
Time
08:45 - 09:45
Location
Salamanca Auditorium (Hall 3)
Chairs
  • Jos Jonkers (Amsterdam, Netherlands)
  • Pierre Saintigny (Lyon, France)
Poster Discussion 1 – Translational research Poster Discussion session

91PD - Raman microscopy for the identification of an aggressive variant of prostate cancer, intraductal carcinoma of the prostate (ID 2734)

Presentation Number
91PD
Lecture Time
08:45 - 08:45
Speakers
  • Dominique Trudel (Montreal, Canada)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

Prostate cancer (PC), initially diagnosed on biopsies by pathologists, is the most frequent cancer in North American men. However, better tools are needed for pathologists to diagnose intraductal carcinoma of the prostate (IDC), an aggressive histopathological variant of PC for which therapeutic options are now available. Indeed, no technique or biomarker is clinically available to support the diagnosis of IDC. Raman spectroscopy (RS) provides a global molecular characterisation of the tissue by analysing how photons interact with the molecules present in the tissue. Indeed, we and other groups previously used RS to detect cancer from multiple organ types, machine learning classification models being employed to process the complex Raman data.

Methods

We used Raman micro-spectroscopy (RµS) to detect IDC on tissues from 483 first-line radical prostatectomies from three Canadian institutions. Following a rapid, standardized and low-cost protocol, we acquired an average of 7 Raman spectra per patient and generated classification models using machine learning technology. Importantly, models were trained with data from one institution before independent testing on the data from the other two institutions.

Results

The three institutions included 272, 76 and 135 patients. Median age at diagnosis ranged from 61-62 years-old, with median pre-operative PSA ranging from 6.6-7.4 µg/L. Most patient had ≤3 + 4 Gleason score (60-80% of the specimens) and pT3-stage incidence was 31-55%. IDC was identified in 6-18% of the patients of each cohort. Overall, we acquired an average of 7 Raman spectra per patient. In the training cohort (N = 272), RµS identified IDC with a sensitivity of 95%, a specificity of 94% and an accuracy of 94%. Results from the testing cohort were in a similar range, with sensitivities of 88 and 92%, specificities of 83 and 91% and accuracies of 85 and 91%.

Conclusions

As clinically available biomarkers of IDC have reported sensitivities/specificities of ∼80%, we here identified IDC with accuracies ≥85%. Since our classification model was trained on a cohort and independently tested on the other two, these are likely to be close to real life experience making clinical implementation a realistic outcome.

Legal entity responsible for the study

The authors.

Funding

Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM, continuum program) IVADO, Institut de valorisation des données.

Disclosure

All authors have declared no conflicts of interest.

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Poster Discussion 1 – Translational research Poster Discussion session

LBA16 - TCR-beta repertoire convergence and evenness are associated with response to immune checkpoint inhibitors (ID 5435)

Presentation Number
LBA16
Lecture Time
08:45 - 08:45
Speakers
  • Philip Jermann (Basel, Switzerland)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

Immune checkpoint inhibitors (ICI) significantly improve clinical outcome of advanced non-small cell lung cancer (NSCLC) patients. However, as only a subset of patients responds to treatment, there is an urgent need for predictive biomarkers. Here we investigated the association of TCR-beta (TCRB) clonal expansion and convergence with treatment response. We assessed these features within the tumor microenvironment of treatment naïve patients and compared their predictive value with other biomarkers such as tumor mutational burden (TMB) and PD-L1 status.

Methods

Total RNA was extracted from NSCLC FFPE pretreatment tissue biopsies of patients receiving ICI therapy (n = 45). TCRB repertoire NGS libraries were prepared with the Oncomine TCRB-SR assay and sequenced on the Ion Torrent instrument. TCR convergence (=frequency of clonotypes identical in amino acid but different in nucleotide space) and clonal evenness (=measurement of the similarity of clone sizes) were evaluated independently using Fisher’s test. TMB values from the same biopsies were assessed from extracted genomic DNA via the Oncomine Tumor Mutation Load Assay. PD-L1 status was determined by immunohistochemical staining.

Results

Durable clinical benefit from ICI therapy was associated with increased TCR convergence (p = 0.12) and decreased clonal evenness (p = 0.01) independently. The TCR-based patient classification was able to identify responders who otherwise had low to intermediate (<9 Mutations per Mb) TMB or negative (<1%) PD-L1 status. Adding TCR evenness to TMB and PD-L1-based stratification allowed for the identification of 82% of responders, compared to 47% for TMB alone and to the identification of 94% of responders, compared to 59% for PD-L1 alone.

Conclusions

Our results show that evaluation of the TCR-beta repertoire in NSCLC specimens is an effective tool to stratify patients according to their response to ICI therapy. In particular, TCR assessment identifies subpopulations of responding patients that would otherwise be misclassified by either TMB or PD-L1 status. Thus, combinatorial use of several biomarkers may yield the highest clinical accuracy for ICI therapy selection.

Legal entity responsible for the study

Philip Jermann.

Funding

Thermo Fisher Scientific.

Disclosure

P. Jermann: Honoraria (self), Research grant / Funding (institution), Travel / Accommodation / Expenses: Thermo Fisher Scientific; Research grant / Funding (institution): BMS. K. Leonards: Research grant / Funding (institution): Thermo Fisher Scientific; Research grant / Funding (institution): Bristol-Myers Squibb. T. Looney: Full / Part-time employment: Thermo Fisher Scientific. I. Alborelli: Research grant / Funding (institution), Travel / Accommodation / Expenses: Thermo Fisher Scientific; Research grant / Funding (institution): Bristol-Myers Squibb. S.I. Rothschild: Honoraria (self), Research grant / Funding (institution): AstraZeneca; Honoraria (self), Research grant / Funding (institution): BMS; Research grant / Funding (institution): Merck Serono; Honoraria (self): MSD; Honoraria (self): Roche; Honoraria (self): Novartis. S. Savic Prince: Honoraria (self), Advisory / Consultancy: MSD; Advisory / Consultancy: AstraZeneca; Honoraria (self): Roche. A. Zippelius: Advisory / Consultancy: BMS; Advisory / Consultancy, Research grant / Funding (institution): Roche; Advisory / Consultancy: MSD; Advisory / Consultancy: NBE Therapeutics; Research grant / Funding (institution): Secarna; Research grant / Funding (institution): Beyondsprings; Research grant / Funding (institution): Crescendo; Research grant / Funding (institution): Hookipa. L. Bubendorf: Honoraria (self), Research grant / Funding (institution): Roche; Honoraria (self), Research grant / Funding (institution): MSD; Honoraria (self): BMS; Honoraria (self): AstraZeneca. All other authors have declared no conflicts of interest.

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Poster Discussion 1 – Translational research Poster Discussion session

1875PD - Targeting molecular mediators of T cell exclusion for effective immunotherapy in ovarian cancer (ID 2267)

Presentation Number
1875PD
Lecture Time
08:45 - 08:45
Speakers
  • Yulei Wang (South San Francisco, United States of America)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on large ovarian tumour cohorts, here we report classification and functionally dissection of tumour-immune contexture in human ovarian cancer.

Methods

CD8 IHC and RNAseq analysis were performed on 370 ovarian tumours from the ICON7 phase III clinical trial. Coupling digital pathology with transcriptome analysis, a random forest machine learning algorithm was developed and independently validated for classifying tumour-immune phenotypes in ovarian cancer. Anti-tumour activity of TGFβ blockade in combination with anti-PD-L1 was evaluated in an ovarian cancer mouse model.

Results

We show the identified tumour-immune phenotypes are of biological and clinical importance with interconnection to molecular subtypes and association with clinical outcome in ovarian cancer. Two important hallmarks of T cell exclusion were identified: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFβ and activated stroma. We identified TGFβ as a key mediator of T cell exclusion. TGFβ reduced MHC class I expression in ovarian cancer cells and induced extracellular matrix (ECM) production and immunosuppressive molecules in human primary fibroblasts. Finally, we demonstrated that combination of anti-TGFβ and anti-PD-L1 in a mouse ovarian cancer model significantly improved the anti-tumour efficacy and survival.

Conclusions

This study provided the first systematic and in-depth characterization of the molecular features and mechanisms underlying the tumour-immune phenotypes in ovarian cancer. We illuminated a multi-faceted role of TGFβ in mediating consequential crosstalk between tumour cells and cancer associated fibroblasts to shape the tumour-immune contexture. Our findings support that targeting the TGFβ pathway represents a promising therapeutic strategy to overcome T cell exclusion and optimize response to cancer immunotherapy.

Legal entity responsible for the study

The authors.

Funding

Genentech/Roche.

Disclosure

All authors have declared no conflicts of interest.

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Poster Discussion 1 – Translational research Poster Discussion session

1876PD - Immunogenicity of BRCA1-deficient ovarian cancers is driven through DNA sensing and is augmented by PARP inhibition (ID 4983)

Presentation Number
1876PD
Lecture Time
08:45 - 08:45
Speakers
  • Marine Bruand (Epalinges, Switzerland)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

BRCA1 is an essential gene of the homologous recombination repair pathway. Ovarian cancers with BRCA1 mutations represent about 20% of HGSOC and are characterized by loss-of-function TP53 mutations, copy number alterations, chromosomal instability, high neoantigen loads and increased infiltration of intraepithelial CD8 tumor-infiltrating lymphocytes.

Methods

To address this hypothesis, we investigated the effects of BRCA1 loss on tumor immunogenicity in human and mouse ovarian cancer BRCA1 isogenic cell lines. We further studied tumor immunogenicity and immune recognition in situ in human ovarian carcinomas and in vivo using syngeneic transplantable Tp53-/-BrcaWT and Tp53-/-Brca1-/- mouse models.

Results

We propose that DNA damage induced by BRCA1 loss could be a tumor-autonomous inflammatory mechanism. Our hypothesis was corroborated by studies in human and mouse isogenic ovarian cancer cell lines which revealed that BRCA1 deficiency leads to increased cytoplasmic translocation of nuclear DNA, increased DNA sensing, induction of proinflammatory cytokines and T cell recruiting chemokines and increased tumor CD8 T cell infiltration. PARP inhibition exacerbated type I IFN responses in BRCA1-deficient ovarian cancer cell lines and simultaneously increased surface expression of PDL1. Increased DNA damage, as measured by γH2AX tumor staining, was also detected in situ in human ovarian cancers with BRCA1 mutations. Importantly, we detected tumor expression of pSTAT1 confirming a type I IFN activation in tumors with DNA damage. Both DNA damage and pSTAT1 activation correlated with higher TIL infiltration and better overall survival. Our results translated in mouse models of ovarian cancer where Trp53-/-Brca1-/- but not Trp53-/-Brca1WT tumors presented with biomarkers of DNA damage, type I IFN pathway activation and responded to a therapeutic combination of PARP inhibitor Olaparib with dual checkpoint blockade antibodies.

Conclusions

Our results provide a mechanistic link between loss of BRCA1 and induction of tumor-driven inflammatory and immunogenic responses in ovarian cancer that was mediated by tumor-cell autonomous type I IFN signaling, which translated to increased immune surveillance by CD8 T cells.

Legal entity responsible for the study

George Coukos.

Funding

This study was supported by the Ludwig Institute for Cancer Research and grants P50 CA083638 SPORE in Ovarian Cancer, the Emma Mouschamp Foundation, the Porphyrogenis Fundation and by a Stand Up To Cancer-Ovarian Cancer Research Fund Alliance-National Ovarian Cancer Coalition Dream Team Translational Cancer Research Grant (SU2C-AACRDT16- 15, to EMS). Stand Up To Cancer is a division of the Entertainment 2 Industry Foundation. Research grants are administered by the American Association for Cancer Research, the Scientific Partner of SU2C.

Disclosure

All authors have declared no conflicts of interest.

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Poster Discussion 1 – Translational research Poster Discussion session

Invited Discussant 91PD, LBA16, 1875PD and 1876PD (ID 6947)

Lecture Time
08:45 - 09:05
Speakers
  • Jos Jonkers (Amsterdam, Netherlands)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45
Poster Discussion 1 – Translational research Poster Discussion session

Q&A led by Discussant (ID 6949)

Lecture Time
09:05 - 09:15
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45
Poster Discussion 1 – Translational research Poster Discussion session

LBA17 - Harmonization study of tumour mutational burden determination in non-small cell lung cancer (NSCLC) (ID 5443)

Presentation Number
LBA17
Lecture Time
09:15 - 09:15
Speakers
  • Eva M Garrido-Martin (Madrid, Spain)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

Tumour mutational burden (TMB) is an emerging predictive biomarker for patients with NSCLC treated with checkpoint inhibitors. A number of gene panels are available for TMB calculation, each with different characteristics, including the number of genes and the selected individual genes, and distinct informatics algorithms that may lead to different results. We have performed a correlation study of 3 panels in a large cohort of clinically annotated NSCLC patients.

Methods

We have blindly evaluated the concordance of tissue TMB assessments of two different commercially available panels: TSO500 (performed at HU 12 de Octubre) and Oncomine TML (performed at CIOCC), with Foundation One® CDx (F1CDx-Penzberg, Germany). A cohort of 100 early stage NSCLC tumour samples is being utilized. PD-L1 expression was analyzed in all samples with 22C3 PharmDX.

Results

The determination of TMB for all panels was calculated as total number of mutations (synonym plus non-synonym) per megabase of exonic DNA. Four samples did not have enough sequencing depth for TML panel (n = 96 was used for all correlations). TMB values correlated with F1CDx with a R2 =0.8775 for TSO500; and with a R2 = 0.8119 for TML. The correlation between TSO500 and TML was R2 = 0.8545. Results obtained for each panel are indicated in the table below. Additionally, TMB values were evaluated in the samples grouped by < 1%, >1% and >50% of PD-L1 expression. In tumours PD-L1<1% (n = 55), TMB values correlated with F1CDx with a R2 = 0.9120 (TSO500) and a R2 = 0.8768 (TML), respectively. In tumours PD-L1>1% (n = 41), TMB values correlated with F1CDx with a R2 = 0.7466 (TSO500) and a R2 = 0.5735 (TML), respectively.

LBA17

NSCLC Cohort (n = 96)TSO500TMLF1CDx
Total TMB Range (muts/Mb) Average (muts/Mb) Median (muts/Mb) % of samples with TMB >10 muts/Mb % of samples with TMB >13 muts/Mb % of samples with TMB >16 muts/Mb1-84 13 9 46% 31% 20%0-60 13 10 50% 38% 24%0-74 14 10 51% 35% 28%
PDL1 <1% (n = 55)TSO500TMLF1CDx
TMB high (≥10) TMB med/low (<10)53% 47%64% 36%51% 49%
PDL1 >1% (n = 55)TSO500TMLF1CDx
TMB high (≥10) TMB med/low (<10)59% 41%63% 37%51% 49%
PDL1 >50% (n = 10)TSO500TMLF1CDx
TMB high (≥10) TMB med/low (<10)70% 30%80% 20%40% 60%

Conclusions

There is a strong correlation between TMB determined by TSO500 and TML panels with F1CDx, particularly for tumours with low PD-L1 expression. The range of TMB values is lower with TSO500 and TML, for samples determined TMBhigh by F1CDx. Cut-off values may be lowered for these panels in order to meet F1CDx TMB categories.

Legal entity responsible for the study

Fundacion para la Investigacion Biomedica del Hospital Doce de Octubre, Madrid, Spain.

Funding

Bristol-Myers Squibb.

Disclosure

E.M. Garrido-Martin: Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Bristol-Myers Squibb; Speaker Bureau / Expert testimony: Illumina. S. Hernandez Prieto: Honoraria (institution): Roche; Honoraria (institution): Thermo Fisher; Honoraria (institution), Travel / Accommodation / Expenses: Pfizer; Honoraria (institution): Bristol-Myers Squibb; Honoraria (institution): AbbVie. S. Ponce Aix: Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Roche; Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: MSD; Advisory / Consultancy, Speaker Bureau / Expert testimony, Travel / Accommodation / Expenses: Bristol-Myers Squibb; Travel / Accommodation / Expenses: Lilly; Travel / Accommodation / Expenses: AstraZeneca. P. Garrido: Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (self): Roche; Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony: MSD; Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony: Bristol-Myers Squibb; Advisory / Consultancy, Speaker Bureau / Expert testimony: Boerhinger Ingelheim; Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony: Pfizer; Advisory / Consultancy: AbbVie; Advisory / Consultancy, Research grant / Funding (institution): Guardant Health; Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony: Novartis; Honoraria (institution), Advisory / Consultancy: Lilly; Advisory / Consultancy, Speaker Bureau / Expert testimony: AstraZeneca; Advisory / Consultancy: Janssen; Advisory / Consultancy, Research grant / Funding (institution): Sysmex; Honoraria (institution), Advisory / Consultancy: Blueprint Medicines; Honoraria (institution), Advisory / Consultancy, Speaker Bureau / Expert testimony: Takeda; Speaker Bureau / Expert testimony: Gilead; Speaker Bureau / Expert testimony: Rovi; Honoraria (institution): Pharmamar; Honoraria (institution): Celgene; Honoraria (institution): Sanofi; Honoraria (institution): GSK, Theradex Oncology. F. Lopez-Rios: Honoraria (self), Honoraria (institution), Advisory / Consultancy, Travel / Accommodation / Expenses: Roche; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Travel / Accommodation / Expenses: Thermo Fisher; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Travel / Accommodation / Expenses: Pfizer; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Travel / Accommodation / Expenses: Bristol-Myers Squibb; Honoraria (self), Honoraria (institution), Advisory / Consultancy, Travel / Accommodation / Expenses: AbbVie; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: AstraZeneca; Honoraria (self), Advisory / Consultancy, Travel / Accommodation / Expenses: MSD; Honoraria (self), Advisory / Consultancy: Bayer. L. Paz-Ares: Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Lilly; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution): MSD; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution): Bristol-Myers Squibb; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Roche; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Pharmamar; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Merck; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution): AstraZeneca; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Novartis; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Boehringer; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Celgene; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Servier; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Sysmex; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Amgen; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Incyte; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony, Research grant / Funding (institution): Pfizer; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Sanofi; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Ipsen; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Adacap; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Bayer; Honoraria (self), Advisory / Consultancy, Speaker Bureau / Expert testimony: Blueprint. All other authors have declared no conflicts of interest.

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Poster Discussion 1 – Translational research Poster Discussion session

89PD - Prognostic and predictive impact of high tumor mutation burden (TMB) in solid tumors: A systematic review and meta-analysis (ID 1983)

Presentation Number
89PD
Lecture Time
09:15 - 09:15
Speakers
  • Mairead G. McNamara (Manchester, United Kingdom)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

Immune checkpoint blockade (ICB) has improved overall survival (OS) in selected patients (pts) with cancers, but predictive biomarkers are required. TMB has been proposed as a potential biomarker, but challenges exist as to its optimal definition, quantification and utility.

Methods

A search of Medline and Embase identified studies reporting association of TMB (high vs low) with survival in pts with solid tumors, irrespective of exposure to ICB. The influence of TMB on OS was explored by meta-analysis, utilizing the generic inverse variance method. Association between baseline factors (age, gender, primary tumor site, stage, smoking history, proportion of pts with squamous histology, receipt of ICB) and survival were assessed with mixed effects meta-regression, weighted by study sample size.

Results

Of 493 studies, 35 were eligible (ICB used in 28); 13 prospective, 22 retrospective; correlation between PD-L1 expression and TMB was not possible due to limited reporting studies. Analysis comprised 10,433 pts; median age: 63 yrs (range 53-73; reported in 18 studies). Median proportion male: 62.5% (range 40-83%), primary tumor site lung: 17 studies (9 squamous histology), melanoma: 5, urothelial: 3, breast: 2, head & neck, biliary and hepatocellular carcinoma: all 1, multiple sites: 5. Eleven different assays for TMB determination were utilized (Foundation One in 15 studies). Amongst 22 studies, where reported, 5 different TMB definitions were used, with only 10 studies reporting a median TMB (Mut/Mb); 11 different TMB “high” thresholds were reported. In the absence of ICB, high TMB was associated with increased risk of death (HR 2.87, 95% CI 1.41-5.82, p=.004). In the presence of ICB, high TMB was associated with improved OS (HR 0.60, 95% CI 0.42-0.86, p=.005), albeit with significant heterogeneity (p=.002). Studies with a higher proportion of male pts had increased hazard of death (β=.75) and those with a higher proportion of pts receiving ICB had a lower hazard of death (β=-.56).

Conclusions

High TMB is a poor prognostic factor in solid tumors, but is predictive of improved OS with ICB. Standardization of TMB analysis/reporting is imperative for reliable clinical application.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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Poster Discussion 1 – Translational research Poster Discussion session

90PD - Comparison of platforms for determining tumour mutational burden (TMB) in patients with non-small cell lung cancer (NSCLC) (ID 2699)

Presentation Number
90PD
Lecture Time
09:15 - 09:15
Speakers
  • Jonathan Baden (Princeton, NJ, United States of America)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

TMB has been associated with response to immune checkpoint inhibitors in clinical studies and has been investigated as a biomarker for first-line (1L) treatment with nivolumab + ipilimumab (N+I) in patients with NSCLC. TMB can be measured by whole exome sequencing (WES) or estimated using targeted gene panels. Clinical implementation of TMB assays can be facilitated by standardization of methods and concordance across platforms. We compared TMB results in commercial and clinical samples from patients with NSCLC using WES, the in vitro diagnostic FoundationOne CDx™ (F1CDx), and the research use only assay TruSight™ Oncology 500 (TSO500).

Methods

TMB was evaluated in serial, formalin-fixed, paraffin-embedded sections from 98 procured NSCLC samples using WES (captures coding regions from all genes; ∼30 megabases [Mb]), F1CDx (324 genes; ∼0.8 Mb), and TSO500 (523 genes; ∼1.3 Mb). TMB scores were reported as mutations/Mb (mut/Mb) and compared by Spearman’s correlation. Association of TMB with response was assessed in a subset of 59 patients who had NSCLC treated with 1L N+I (CheckMate 568 [NCT02659059]) and had data from both F1CDx and TSO500.

Results

TMB estimates from F1CDx and TSO500 correlated highly with WES (r = 0.83 and 0.86, respectively; P < 0.001 for both). Accounting for different calculation methods used for each assay, the clinically relevant cutoff for high TMB (TMB-H) for 1L N+I in NSCLC patients of 10.0 mut/Mb by F1CDx projected to 7.7 mut/Mb (95% CI, 7.1–8.3) by WES and 12.3 mut/Mb by TSO500. Overall percentage agreements around these cutoffs were 86% for WES vs F1CDx and 83% for WES vs TSO500. TMB estimates from F1CDx and TSO500 correlated well (r = 0.84; P < 0.001). In patients treated with N+I, 8/10 responders and 16/38 nonresponders were identified as TMB-H by F1CDx and 7/10 responders and 12/38 nonresponders by TSO500.

Conclusions

TMB data from WES, F1CDx, and TSO500 correlated well in commercial and clinical NSCLC samples. More responders than nonresponders to N+I were identified as TMB-H but with similar frequencies when assessed by F1CDx or TSO500. This study demonstrates the feasibility of TMB harmonization and bridging of TMB cutoffs across testing platforms.

Clinical trial identification

(NCT02659059).

Editorial acknowledgement

Amrita Dervan, PhD, and Jay Rathi, MA, of Spark Medica Inc, funded by Bristol-Myers Squibb.

Legal entity responsible for the study

Bristol-Myers Squibb.

Funding

Bristol-Myers Squibb.

Disclosure

J. Baden: Shareholder/Stockholder/Stock options, Full/Part-time employment: Bristol-Myers Squibb; Shareholder/Stockholder/Stock options: Johnson & Johnson. C. Zhao: Shareholder/Stockholder/Stock options, Full/Part-time employment: Illumina Inc. J. Pratt: Shareholder/Stockholder/Stock options, Full/Part-time employment: Bristol-Myers Squibb. S. Kirov: Shareholder/Stockholder/Stock options, Full/Part-time employment: Bristol-Myers Squibb. S. Pant: Shareholder/Stockholder/Stock options, Full/Part-time employment: Bristol-Myers Squibb. A. Seminara: Shareholder/Stockholder/Stock options, Full/Part-time employment: Bristol-Myers Squibb. G. Green: Shareholder/Stockholder/Stock options, Full/Part-time employment: Bristol-Myers Squibb. S. Bilke: Shareholder/Stockholder/Stock options, Full/Part-time employment: Illumina Inc. I. Deras: Shareholder/Stockholder/Stock options, Full/Part-time employment: Illumina Inc; Shareholder/Stockholder/Stock options: Bristol-Myers Squibb. D.A. Fabrizio (co-senior author): Shareholder/Stockholder/Stock options: Roche; Full/Part-time employment: Foundation Medicine Inc. T. Pawlowski (co-senior author): Shareholder/Stockholder/Stock options, Full/Part-time employment: Illumina Inc.

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Poster Discussion 1 – Translational research Poster Discussion session

1877PD - Prevalence and prognostic effect of high tumor mutation burden (TMB-H) across multiple less common solid cancers using a real-world dataset (ID 2434)

Presentation Number
1877PD
Lecture Time
09:15 - 09:15
Speakers
  • Daniel Backenroth (New York, NY, United States of America)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45

Abstract

Background

Little is known about the prognostic effect of TMB-H among patients with less common cancers who did not receive an immunotherapy (IO).

Methods

The de-identified Flatiron Health-Foundation Medicine (FMI) Clinico-Genomic Database was used to select patients (pts) with any of 10 solid cancers (Table). 109 Pts with confirmed microsatellite instability-high (MSIH) cancers were excluded, of which 101 pts were endometrial cancer. TMB-H was defined as ≥ 10 mutations per megabase (Mut/Mb) with an additional analysis using a cutoff of 13 Mut/Mb. For overall survival (OS) analysis, Pts with IO were excluded if start of IO earlier than or equal to FMI report date (69 pts), or censored if start of IO later than FMI report date (243 pts). OS was analyzed using Kaplan-Meier method and Cox proportional hazard model, adjusting for age, gender, cancer types, practice type and albumin. A non-inferiority test of TMB-H having longer OS than TMB-low (-L) was carried out with a prespecified hazard ratio (HR) of 0.75.

Results

Of the 2,589 pts (table), average age at diagnosis was 64 years and 65% were female. Median TMB was 2.6 Mut/Mb overall, ranged from 1.7 (Meso, salivary, thyroid) to 8.7 (SCLC) Mut/Mb. Overall 12.8% were TMB-H with the highest in SCLC (40.0%) and lowest in meso (1.2%). The adjusted HR (AHR) of TMB-H vs. -L was 0.94 (95% CI: 0.77-1.13) for OS from FMI report date, which met the prespecified threshold for non-inferiority by rejecting the null hypothesis. The AHR was 0.84 (0.67-1.05) using alternative cutoff of 13 Mut/Mb. Comparable results were observed when including MSI-H pts and calculating OS from 1st observed antineoplastic treatment date.

NTMB-H
OS (month, 95%CI)
HRadjustPadjust
n%TMB-HTMB-L
Total2,58933212.88.4 (7.4; 11.4)10.5 (9.5; 11.5)0.94 (0.77; 1.13)0.491
SCLC30512240.06.4 (5.4; 7.5)7.4 (5.5; 10.5)1.03 (0.74; 1.44)0.863
Neuroendocrine1644829.310.4 (6.4; NA)6.4 (4.5; 10.5)0.83 (0.48; 1.44)0.506
Cervical1141714.9NA (6.4; NA)7.4 (4.4; 11.5)0.32 (0.08; 1.31)0.113
Anal1251713.67.4 (2.5; NA)7.5 (5.5; 15.4)0.84 (0.40; 1.79)0.659
Vulvar30413.38.5 (0.5; NA)6.5 (2.5; NA)1.18 (0.22; 6.29)0.848
Salivary1692213.04.5 (3.5; NA)15.5 (10.5; 21.5)1.20 (0.48; 2.99)0.691
Endometrial5906611.211.4 (8.5; 26.5)13.5 (11.5; 15.4)1.15 (0.75; 1.75)0.522
Biliary706284.011.5 (7.4; NA)8.4 (7.4; 10.4)0.65 (0.35; 1.19)0.162
Thyroid22362.710.2 (1.5; NA)27.5 (21.5; NA)1.64 (0.39; 6.96)0.502
Meso16321.2NA12.5 (8.5; 15.5)-0.997

Conclusions

There is a wide range of TMB among these cancers. Non-inferiority testing and HR estimates comparing OS for TMB-H (≥10 Mut/Mb) vs. -L did not support an effect of TMB on OS in the absence of IO for these cancers. Further research is needed to explore whether the prognostic effect of TMB varies by tumor type or threshold.

Legal entity responsible for the study

Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA.

Funding

Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA.

Disclosure

D. Backenroth: Shareholder / Stockholder / Stock options, Full / Part-time employment: Flatiron Health Inc. C. Shao: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co. G. Li: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. L. Huang: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co.. S.K. Pruitt: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. E. Castellanos: Full / Part-time employment: Flatiron Health Inc.. G.M. Frampton: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. K.R. Carson: Full / Part-time employment: Flatiron Health Inc.. T. Snow: Full / Part-time employment: Flatiron Health Inc.. G. Singal: Full / Part-time employment: Foundation Medicine. D. Fabrizio: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. B.M. Alexander: Shareholder / Stockholder / Stock options, Full / Part-time employment: Foundation Medicine. F.J. Jin: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc.. W. Zhou: Shareholder / Stockholder / Stock options, Full / Part-time employment: Merck & Co., Inc..

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Poster Discussion 1 – Translational research Poster Discussion session

Invited Discussant LBA17, 89PD, 90PD and 1877PD (ID 6948)

Lecture Time
09:15 - 09:35
Speakers
  • Pierre Saintigny (Lyon, France)
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45
Poster Discussion 1 – Translational research Poster Discussion session

Q&A led by Discussant (ID 6950)

Lecture Time
09:35 - 09:45
Location
Salamanca Auditorium (Hall 3), Fira Gran Via, Barcelona, Spain
Date
29.09.2019
Time
08:45 - 09:45