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J.V. Heymach
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MINI 06 - Quality/Prognosis/Survival (ID 111)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Treatment of Localized Disease - NSCLC
- Presentations: 1
- Moderators:R. Meguid, J. Yoshida
- Coordinates: 9/07/2015, 16:45 - 18:15, 605+607
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MINI06.11 - The Influence of Body Mass Index on Overall Survival following Surgical Resection of Non-Small Cell Lung Cancer (ID 2722)
16:45 - 18:15 | Author(s): J.V. Heymach
- Abstract
- Presentation
Background:
Population studies suggest that high body mass index (BMI) correlates with a reduced risk of death from lung cancer. The aim of our study was to evaluate the influence of BMI on long term overall survival (OS) in surgical patients with non-small cell lung cancer (NSCLC).
Methods:
Study population consisted of 1935 patients who underwent surgical resection for lung cancer at MD Anderson Cancer Center between 2000-2014. Patients with perioperative mortality, 90-day mortality, intraoperative transfusion, postoperative ICU days, postoperative pneumonia, and postoperative transfusion were excluded. Study variables included both patient and treatment related characteristics. Univariable and multivariable Cox regression analyses were performed to identify variables associated with overall survival. Propensity matching was performed to compare patients with BMI <25 and BMI≥30 matching on type of surgery, age, gender, histology, and pathological stage.
Results:
On univariable analysis, significant predictors of improved survival were higher BMI, pathologic tumor stage (stage I vs II, III, or IV), type of surgery (lobectomy/pneumonectomy vs wedge resection/segmentectomy), younger age, female gender, and adenocarcinoma histology (vs squamous) (all p<0.05). Patients considered morbidly obese (BMI≥35) had a trend towards better outcomes than those classified as obese (BMI ≥30 and <35), overweight (BMI ≥25 and <30), or healthy weight (BMI<25) (HR 0.727, 0.848, 0.926, and 1, respectively, p=NS). On multivariate analysis, BMI remained an independent predictor of survival (p=0.02, see Table). Propensity matching analysis demonstrated significantly better OS (p=0.008) in patients with BMI≥30 compared to BMI <25 (Figure).Multivariate Cox Regression Model
Figure 1N (%) Overall Survival HR (95% CI) BMI <25 (Reference) ≥25 646 (33.4%) 1289 (66.7%) 1.000 0.833(0.713-0.975) Age Continuous variable Median 66 (13-88) 1.024 (1.015-1.032) Gender Female (Reference) Male 984 (50.9%) 951 (49.1%) 1.000 1.236 (1.061-1.441) Stage I (Reference) II III IV 1149 (59.4%) 431 (22.3%) 299 (15.5%) 56 (2.9%) 1.000 1.839 (1.570-2.271) 2.653 (2.182-3.225) 2.737 (1.934-3.873) Surgery Wedge/Segmentectomy (Reference) Lobectomy/Pneumonectomy 198 (10.2%) 1737 (89.8%) 1.000 0.602 (0.479-0.755) Pre-op therapy No (Reference) Yes 1604 (82.9%) 331 (17.2%) 1.000 1.399 (1.160-1.686) Histology Adenocarcinoma (Reference) Squamous Other 1252 (64.7%) 472 (24.4%) 211 (10.9%) 1.000 1.225 (1.035-1.451) 0.959 (0.747-1.231)
Conclusion:
In a large, single center series, after controlling for disease stage and other variables, higher BMI was associated with improved OS following surgical resection of NSCLC. Further studies are necessary to define the complex relationship between BMI and treatment outcomes.
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MINI 09 - Drug Resistance (ID 107)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:L. Villaruz, J. Minna
- Coordinates: 9/07/2015, 16:45 - 18:15, 205+207
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MINI09.10 - Tumor Angiogenesis in LKB1-Mutant Non-Small Cell Lung Cancer (NSCLC) (ID 3059)
16:45 - 18:15 | Author(s): J.V. Heymach
- Abstract
- Presentation
Background:
LKB1 is a critical regulator of cell growth, metabolism and EMT, and it is mutated in 20-30% of non-small cell lung cancers (NSCLC). LKB1 mutations co-occur with KRAS-activating mutations in 7%-10% of all NSCLC and results in an aggressive phenotype and a worse response to chemotherapy compared to KRAS-mutated tumors. Because LKB1 activates AMPK (AMP-activated protein kinase) which functions as a cellular energy sensor, LKB1-deficient cells are unable to appropriately sense metabolic and energetic stress. LKB1 is also known to regulate angiogenesis, but the mechanism(s) by which this occurs remains unclear. Bevacizumab, the human anti-VEGF antibody approved for the treatment of NSCLC, improves the progression-free and overall survival of NSCLC patients combined with chemotherapy, but often the benefit is transient, and therapeutic resistance occurs. Our laboratory has previously identified phenotypical differences in vasculature patterns in A549 NSCLC tumors resistant to bevacizumab (LKB1 mutant), when compared to H1975 tumors, (LKB1 wild-type). In addition, LKB1 mutant NSCLC cell lines are highly vulnerable to agents acting on energetic pathways. These results may indicate that loss of LKB1 in NSCLC could alter the tumor vasculature and regulate sensitivity to anti-angiogenic therapies. Here, we investigate the hypothesis that combinations of energetic-depleting compounds along with blockade of tumor angiogenesis would be more effective in NSCLC LKB1 mutant tumors.
Methods:
mRNA and protein expression of 584 angiogenesis-related genes were analyzed in wild-type and LKB1 mutant NSCLC (TCGA, RPPA and PROSPECT databases). In vitro validation was performed using qPCR, immunohistochemistry and western blot analysis as well as pairs of isogenic LKB1 mutant cell lines with overexpressed or silenced LKB1. Endothelial cells were incubated with conditioned medium of wild-type and LKB1 mutant NSCLC cell lines, and tube formation matrigel, proliferation and migration (Boyden chamber) assays were performed.
Results:
We identify a group of new and classic angiogenesis-related molecules: VEGFA, VEGFR1, KDR, NRP1, PDGFB, PDGFRA-B, HIF-1A, C-KIT, VCAM1, hypoxia related molecules: HIF1AN, EGLN1, HIF3A, CA12, EPAS1 and immune related molecules: TNFSF11, NFKB1, CD47, PDL1 differentially expressed in LKB1-wild type and LKB1 mutant NSCLC (p<0.05 and fold-change ≥ or ≤1.5). LKB1 mutant cell lines showed higher protein expression of phospho-cKIT, a tyrosine-kinase receptor involve in cell proliferation and angiogenesis, and CA12 (Carbonic anhydrase 12), a known HIF-1α regulated molecule, involved in maintaining cellular pH homeostasis. Also, LKB1 mutant cells exhibit different quantitative vascular patterns in matrigel assays like number of nodes, junctions, length and branching of the endothelial matrix (p<0.05). Human endothelial cells exhibited an increase rate of proliferation and migration when incubated with conditioned medium from LKB1 mutant NSCLC cell lines compared with conditioned media from LKB1-wild type NSCLC cell lines (p<0.05).
Conclusion:
There are biological differences in vasculature patterns in LKB1 mutant NSCLC tumors and in LKB1 mutant cell lines comparing with wild-type LKB1. These differences are translated in biological alterations of human endothelial cells in vitro suggesting an important role of LKB1 in resistance to anti-angiogenic treatments in vivo.
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MINI 27 - Biology and Other Issues in SCLC (ID 152)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Small Cell Lung Cancer
- Presentations: 1
- Moderators:P.A. Bunn, Jr, J. Sage
- Coordinates: 9/09/2015, 16:45 - 18:15, 605+607
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MINI27.01 - Investigation of Chimeric Antigen Receptor T Cells as a Novel Immunotherapy for SCLC (ID 2901)
16:45 - 18:15 | Author(s): J.V. Heymach
- Abstract
- Presentation
Background:
Small cell lung cancer (SCLC) is an aggressive malignancy with an average of 20,000 new cases per year and 16,000 deaths per year. SCLC accounts for about 10-15% of newly diagnosed lung cancers. Even in the face of extensive research, the standard of care- platinum-based combination chemotherapy- has not changed in decades. Yet even with modern chemotherapy formulations, the two year survival rate for advanced disease stages is less than 5%. Complicating treatment is that often at the time of diagnosis, SCLC as already metastasized to the patient’s surrounding lymph nodes. Therefore, a novel therapeutic strategy will have address three disease aspects: (1) reduce primary tumor growth and eliminate metastatic spread; (2) avoid resistance mechanisms used by SCLC to escape radio- and chemotherapies; (3) synergize with or supersede current therapeutic strategies. Chimeric antigen receptor T cells, little explored in SCLC, is well suited to address these aspects.
Methods:
Human SCLC cell lines were analyzed using a 90 gene signature to establish immunological targets. Western blot analysis confirmed the expression of CD56 and other targets on SCLC cell lines. For CAR T cell generation, PBMC were electroporated with the Sleeping Beauty transposase and a transposon containing a CD56R chimeric antigen receptor. CD56R-CAR transduced T cells were cultured for 4 weeks in the presence of K562 cells expressing CD56 and the cytokines IL-2/IL-21 to expand CD56R-CAR T cells. CAR T cells were tested in vitro for killing ability in the presence of three SCLC cell lines using a chromium release assay. CAR T cells were also analysed via FACS to assess CAR expression, T cell phenotype, and memory status.
Results:
An analysis of immune markers in SCLC cell lines revealed that, compared to NSCLC lines, there is a reduction in the expression of suppressive ligands and co-stimulatory ligands, antigen presentation, and natural killer ligands. SCLC cell lines, however, express high levels of CD56. When two CD56-positive and one CD56-negative cell line was tested, CD56-CAR T cells could kill efficiency CD56 expressing cell lines, however there was little killing of the CD56-negative cell line. An analysis of PBMCs cultured after electroporation revealed that a large percentage of CD3+ T cells expressed the CD56 CAR and even after 4 weeks in culture, the CAR T cells displayed a memory phenotype.
Conclusion:
An interrogation of SCLC cell lines versus NSCLC cell lines revealed that SCLC cell lines had reduced expression of checkpoint ligands, NK cell killing ligands, antigen presentation, but consistent with their origin, high expression of CD56. Our conclusion from this analysis is that expansion of SCLC-specific immune responses in vivo or elicitation of de novo responses in vivo will be hindered. Therefore, immunotherapies centered around adoptive transfer of T cell that can kill in an HLA-independent manner maybe better suited for SCLC. In that vein, CD56R-CAR T cells effectively targeted CD56-positive SCLC in vitro, but was unable to kill CD56-negative cells- which indicates a possible escape variant. Our lab is now moving toward testing CD56R-CAR T cell in vivo in both xenograph models and spontaneous ones.
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MINI 30 - New Kinase Targets (ID 157)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Treatment of Advanced Diseases - NSCLC
- Presentations: 1
- Moderators:K. Park, M. Villalona
- Coordinates: 9/09/2015, 18:30 - 20:00, Four Seasons Ballroom F3+F4
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MINI30.15 - Discussant for MINI30.11, MINI30.12, MINI30.13, MINI30.14 (ID 3552)
18:30 - 20:00 | Author(s): J.V. Heymach
- Abstract
- Presentation
Abstract not provided
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MS 03 - Is Tumor Angiogenesis Still a Viable Target in Advanced NSCLC? (ID 21)
- Event: WCLC 2015
- Type: Mini Symposium
- Track: Treatment of Advanced Diseases - NSCLC
- Presentations: 1
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MS03.01 - Current Understanding of the Biology (ID 1856)
14:15 - 15:45 | Author(s): J.V. Heymach
- Abstract
- Presentation
Abstract not provided
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ORAL 13 - Immunotherapy Biomarkers (ID 104)
- Event: WCLC 2015
- Type: Oral Session
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:D. Kim, D. Grunenwald
- Coordinates: 9/07/2015, 16:45 - 18:15, Four Seasons Ballroom F3+F4
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ORAL13.07 - EMT Is Associated with an Inflammatory Tumor Microenvironment with Elevation of Immune Checkpoints and Suppressive Cytokines in Lung Cancer (ID 2134)
16:45 - 18:15 | Author(s): J.V. Heymach
- Abstract
- Presentation
Background:
Promising results in the treatment of NSCLC have been seen with immunomodulatory agents targeting immune checkpoints, such as programmed cell death 1 (PD-1) or programmed cell death 1 ligand (PD-L1). However, only a select group of patients respond to these interventions. The identification of biomarkers that predict clinical benefit to immune checkpoint blockade is critical to successful clinical translation of these agents. Epithelial-mesenchymal transition (EMT) is a key process driving metastasis and drug resistance. Previously we have developed a robust EMT gene signature, highlighting differential patterns of drug responsiveness for epithelial and mesenchymal tumor cells.
Methods:
We conducted an integrated analysis of gene expression profiling from three independent large datasets, including The Cancer Genome Atlas (TCGA) of lung and two large datasets from MD Anderson Cancer Center, Profiling of Resistance patterns and Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax (named PROSPECT) and the Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (named BATTLE-1). Comprehensive analysis of mRNA gene expression, reverse phase protein array (RPPA), immunohistochemistry, in vivo mouse models and correlation with clinical data were performed.
Results:
EMT is highly associated with an inflammatory tumor microenvironment in lung adenocarcinoma, independent of tumor mutational burden. We found immune activation co-existent with elevation of immune checkpoint molecules, including PD-L1, PD-L2, PD-1, TIM-3, BTLA and CTLA-4, along with increases in tumor infiltration by CD4+Foxp3+ regulatory T cells in lung adenocarcinomas that displayed an EMT phenotype. Similarly, IL-6 and indoleamine 2, 3-dioxygenase (IDO) were elevated in these tumors. We demonstrate that in murine models of lung adenocarcinoma, many of these changes are recapitulated by modulation of the miR-200/ZEB1 axis, a known regulator of EMT. Furthermore, B7-H3 is found to negatively correlate with overall survival and recurrence free survival, indicating a potential new therapeutic target in lung adenocarcinoma in the future.
Conclusion:
EMT, commonly related to cancer metastasis and drug resistance, is highly associated with an inflammatory tumor microenvironment with elevation of multiple targetable immune checkpoints and that is regulated at least in part by the miR-200/ZEB1 axis. These findings suggest that EMT may have potential utility as a biomarker selecting patients more likely to benefit from immune checkpoint blockade agents and other immunotherapies in NSCLC and possibly a broad range of other cancers.
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ORAL 21 - Biology - Moving Beyond the Oncogene to Oncogene-Modifying Genes (ID 118)
- Event: WCLC 2015
- Type: Oral Session
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:A. Katz, M.S. Tsao
- Coordinates: 9/08/2015, 10:45 - 12:15, Mile High Ballroom 4a-4f
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ORAL21.02 - Landscape and Functional Significance of KRAS Co-Mutations in Lung Adenocarcinoma (LUAC) (ID 3224)
10:45 - 12:15 | Author(s): J.V. Heymach
- Abstract
- Presentation
Background:
The biological heterogeneity of KRAS-mutant LUAC represents a major impediment to the successful implementation of targeted therapeutic strategies for this clinically challenging group of lung cancer patients. Through integrative, multi-platform analysis of large scale omics data we recently identified three major subsets of KRAS-mutant LUAC defined on the basis of co-occurring genomic alterations in STK11/LKB1 (KL subgroup), TP53 (KP) and CDKN2A/B (KC), the latter coupled with low expression of the TTF1 transcription factor. We further demonstrated subset-specific molecular dependencies, patterns of immune system engagement and therapeutic vulnerabilities. Here, we extend these findings through comprehensive analysis of a wide panel of KRAS co-mutations and assess the impact of key co-mutations on facets of the malignant phenotype including flux through the MAPK and PI3K/AKT pathways and heterotypic interactions with the host immune system.
Methods:
Our datasets consisted of 431 tumors from TCGA (122 KRAS-mutant), 41 additional chemo-naive KRAS-mutant LUACs (PROSPECT dataset) and 36 platinum-refractory KRAS-mutant LUACs from the BATTLE-2 clinical trial. Significant KRAS co-mutations were identified on the basis of a P value threshold of ≤0.05 (Fisher’s exact test) coupled with a baseline prevalence of ≥3%. RNASeq data were downloaded directly from the TCGA site. Expression profiling of PROSPECT tumors was performed using the Illumina Human WG-6 v3 BeadChip Array whereas BATTLE-2 tumors were profiled using the GeneChipâHuman Gene 1.0 ST Array from Affymetrix. Generation of MAPK and PI3K proteomic scores, based on Reverse Phase Protein Array (RPPA) data, has been previously reported.
Results:
Our analysis identified somatic mutations in 31 genes as significantly co-mutated with KRAS in LUAC samples. Among them, co-mutations in STK11/LKB1 (P=0.00011) and ATM (P=0.0004) predominated. Somatic mutations in ERBB4 (P=0.0059), encoding a member of the ErbB family of receptor tyrosine kinases and MAP3K4 (P=0.0017) were also enriched in KRAS-mutant LUAC. We assessed the impact of KRAS co-mutations on the amplitude and directionality of signaling downstream of mutant KRAS using the proteomic “MAPK score“ and “PI3K score” as surrogates of effector pathway activation. Interestingly, co-mutations in ERBB4 were associated with significantly suppressed flux through the MAPK pathway (P=0.0024, t-test). Somatic mutations in other genes, including CAMSAP2, were associated with suppressed signaling through both the MAPK (P=0.00876, t-test) and PI3K-AKT (P=0.0032, t-test) cascades. Finally, within KRAS-mutant tumors, co-mutations in NLRC5, a master transcriptional regulator of MHC Class I molecules were associated with reduced mRNA expression of several of its classical target genes. In addition, low mRNA expression of NLRC5 correlated strongly with reduced expression of key components of the antigen presentation pathway across multiple independent datasets of chemotherapy naïve and platinum refractory KRAS-mutant tumors and cell lines. Thus, in addition to cell autonomous effects, co-mutations can also impinge on the reciprocal relationship between malignant cells and their immune microenvironment.
Conclusion:
Our work identifies a compendium of KRAS co-mutations that impact classical and emerging cancer hallmarks, including evasion of the host immune response. Systematic interrogation of the functional impact of prevalent KRAS co-mutations is essential for the development of personalized treatment approaches for this heterogeneous group of tumors.
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P2.01 - Poster Session/ Treatment of Advanced Diseases – NSCLC (ID 207)
- Event: WCLC 2015
- Type: Poster
- Track: Treatment of Advanced Diseases - NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.01-041 - MD Anderson Oncology Expert Advisor™ System (OEA™): A Cognitive Computing Recommendations Application (App) for Lung Cancer (ID 3106)
09:30 - 17:00 | Author(s): J.V. Heymach
- Abstract
Background:
The OEA[TM] is a clinical support system with a continuous improvement capability. Its objectives are to enable/empower evidence-based decisions/care by disseminating knowledge and expertise to physicians/users tailored to meet the clinical needs of individual patients as if consulting with an expert. Cognitive computing platforms have the potential to disseminate expert knowledge and tertiary level care to patients. This objective is made possible by making available to physicians/providers cognitive computing generated expert recommendations in diagnosis, staging and treatment. The cognitive computing software was trained by MD Anderson experts using currently available consensus guidelines and an iterative feedback process. Here we test the capability of this cognitive computing software program developed at MD Anderson to generate expert recommendations when patients with advanced-stage NSCLC have a targetable molecular aberration.
Methods:
We developed a web based prototype of MD Anderson’s Oncology Expert Advisor (OEA[TM]), a cognitive clinical decision support tool powered by IBM Watson. The Watson technology is IBM’s third generation cognitive computing system based on its unique capabilities in natural language processing and deep QA (question-answer). We trained OEA[TM] by loading historical patient cases and assessed the accuracy of targeted treatment suggestions using MD Anderson’s physicians’ decisions as benchmark. A false positive result was defined as a treatment recommendation rendered with high confidence that was non-correct (less optimal), whereas false negative was defined as a correct or more optimal treatment suggestion listed as a low confidence recommendation.
Results:
In our preliminary analyses, OEA[TM] demonstrated four core capabilities: 1) Patient Evaluation through interpretation of structured and unstructured clinical data to create a dynamic case summary with longitudinal view of the pertinent events 2) Treatment and management suggestions based on patient profile weighed against consensus guidelines, relevant literature, and MD Anderson expertise, which included approved therapies, genomic based therapies as well as automated matching to appropriate clinical trials at MD Anderson, 3) Care pathway advisory that alerts the user for anticipated toxicities and its early identification and proactive management, and 4) Patient-oriented research functionalities for identification of patient cohorts and hypothesis generation for future potential clinical investigations. Detailed testing continues and the accuracy of standard-of-care (SOC) treatment recommendations of OEA[TM], as well as false positivity and negativity rates will be presented in detail at the meeting.
Conclusion:
OEA[TM] is able to generate dynamic patient case summary by interpreting structured and unstructured clinical data and suggest personalized treatment options. Live system evaluation of OEA[TM] is ongoing and the application of OEA[TM] in clinical practice is expected to be piloted at our institution.
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P2.03 - Poster Session/ Treatment of Locoregional Disease – NSCLC (ID 213)
- Event: WCLC 2015
- Type: Poster
- Track: Treatment of Locoregional Disease – NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.03-017 - Pre-Operative Chemotherapy Followed by Surgery for N2 Non-Small Cell Lung Cancer: A 15-Year Experience (ID 3152)
09:30 - 17:00 | Author(s): J.V. Heymach
- Abstract
Background:
The ideal approach to patients with N2 non-small cell lung cancer (NSCLC) remains controversial. While pathological confirmation of nodal status is advocated, in clinical practice patients with suspicious radiographic evidence of N2 disease are frequently assigned to pre-operative therapy without pathological confirmation. Herein, we review our experience with pre-operative chemotherapy followed by surgery in patients with N2 NSCLC and compare outcomes of biopsy proven N2 disease and those patients who were diagnosed based on PET/CT alone.
Methods:
A prospectively entered institutional database was accessed to identify all patients with N2 NSCLC treated by pre-operative chemotherapy followed by surgery from 1999 to 2014. Data were verified by chart review. Patients without biopsy or PET-based evidence of N2 disease were excluded.
Results:
We identified 113 patients of whom 57 had biopsy proof of cN2 and 56 were cN2 based on PET-positivity. See Table 1 for patient demographic and clinico-pathologic variables. Median survival for the cohort was 53.3 months and there was only 1 (0.88%) peri-operative death at 90 days. Three and 5-year survival rates were 63.8% and 39.7%, respectively. Locoregional recurrences occurred in 16.8% of patients. Induction chemotherapy resulted in a significant PET response (SUV reduction > 6) in 38.5% of cases (15/39) where pre- and post-treatment imaging was available. Only 8.77% of patients remained pN2 after pre-operative chemotherapy in those patients who had pre-treatment pathological confirmation. No survival differences were noted between patients with biopsy proven N2 and those with PET-positive N2 nodes (Figure 1).Demographic and clinico-pathologic variables.
Figure 1Variables Biopsy proven N2 (N=57) PET positive N2 (N=56) P value Total cohort (N=113) Median age (range) 64(38-80) 62(43-77) 0.763 63(38-80) Male gender 25(46.3) 28(54.90) 0.378 53(50.48) Mean FEV1 (%pred) 85.78 86.54 0.798 86.16 Mean DLCO (%pred) 81.89 82.28 0.916 82.08 Type of surgery 0.743 Wedge/Segmentectomy 3(5.26) 4(7.14) 7(6.19) Lobectomy 48(84.21) 44(78.57) 92(81.42) Pneumonectomy 6(10.53) 8(14.29) 14(12.39) Post-operative treatment 0.094 None 24(42.11) 27(48.21) 51(45.13) Chemo 1(1.75) 15(26.79) 6(5.31) Radiation 6(5.31) 9(16.07) 41(36.28) Chemoradiation 6(10.53) 9(16.07) 9(16.07) Pathological N stage 0.090 N0 20(35.09) 22(39.29) 42(37.17) N1 32(56.14) 22(39.29) 54(47.79) N2 5(8.77) 12(21.43) 17(15.04)
Conclusion:
Pre-operative chemotherapy followed by surgery for N2 NSCLC in a well-selected cohort results in good short and long-term outcomes. When pathological confirmation of N2 disease requires invasive staging, it may be acceptable to forgo such tests without compromising patient outcomes. Further prospective studies are needed to determine the ideal treatment regimen for these complex patients.
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P2.04 - Poster Session/ Biology, Pathology, and Molecular Testing (ID 234)
- Event: WCLC 2015
- Type: Poster
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P2.04-066 - Programmed Cell Death Ligand 1 (PD-L1) Overexpression and Low Immune Infiltrate Score Correlate with Poor Outcome in Lung Adenocarcinoma (ID 776)
09:30 - 17:00 | Author(s): J.V. Heymach
- Abstract
Background:
PD-L1 is a key immunoregulatory checkpoint which suppresses cytotoxic immune response in a variety of physiologic and pathologic conditions. Thus, inhibition of PD-L1 can lead to reactivating tumor immunity and assist to cancer therapy. PD-L1 overexpression in the tumor cells has been correlated to a lessened immune response and consequent worse prognosis in a variety of cancers. To better understand the immune profiling of PD-L1 expression and its interplay with immune cells, we analyzed the correlation between image analysis-based immunohistochemical (IHC) expression of PD-L1 and tumor infiltrating immune cells density in surgically resected non-small cell lung carcinomas (NSCLC), and the correlation with clinical and pathological features, including patient outcome.
Methods:
IHC for PD-L1, PD-1, CD3, CD4, CD8, CD45RO, CD57, CD68, Granzyme B and FOXP3 were performed in 254 surgical resected stages I-III NSCLC, Adenocarcinoma (ADC=146) and Squamous cell Carcinoma (SqCC=108) from formalin-fixed and paraffin-embedded tissues. PD-L1 membrane expression on tumor cells and density of inflammatory cells were quantified using image analysis in intra-tumoral (IT) and peri-tumoral (PT) compartments. H-score > 5 was used as a cut-off for positive PD-L1 expression and an immune-score (IMS) using CD8/CD4/CD68 was devised. PD-L1 expression and inflammatory cells were correlated with clinico-pathologic features and patient outcomes.
Results:
Positive PD-L1 expression was seen in 26.84% (n=69) of the entire cohort, 23.29% (n=34) of 146 ADC and 23.40% (n=35) of 115 SqCC. In ADC, higher levels of PD-L1 expression were detected in tumors with solid histology pattern compared with other histology patterns (P=0.034), and in lifetime smokers compared with non-smokers (P<0.0001). In SqCC PD-L1 expression was positive correlation with tumor size (Rho=0.19471, P=0.0435). In overall, PD-L1 expression correlated positively with inflammatory cell density in both IT and PT compartments in ADC and SqCC. Patients with KRAS mutation (P=0.00058), solid tumor (P<0.0001) or smoker (P = 0.0446) were more likely to have positive PD-L1 expression tumor cells in ADC. No correlation was detected between EGFR mutation and immune markers. Using PD-L1 and CD8/CD4/CD68 IMS expression levels, in ADC and SqCC, we identified 4 groups of tumors (Table 1). Multivariate Cox proportional hazard regression analysis demonstrated that tumors with high PD-L1 expression and low IMS in ADC exhibited significantly poor recurrence-free (HR=4.299; P=0.0101) and overall survival (HR=5.632; P=0.0010).Table 1. Summary of the correlation between PD-L1 expression levels and immune-score (IMS=CD8/CD4/CD68) in adenocarcinoma (ADC) and squamous cells carcinoma (SQCC).
PDL-1 H-score (ADC) IMS (Low) IMS (High) Total <5 61 (41.78%) 51 (34.93%) 112 (76.71%) ≥5 8 (5.48%) 26 (17.81%) 34 (23.29%) Total 69 (47.26%) 77 (52.74%) 146 (100.0%) PDL-1 H-score (SqCC) <5 37 (34.30%) 36 (33.30%) 73 (67.60%) ≥5 17 (15.70%) 18 (16.70%) 35 (32.40%) Total 54 (50.00%) 54 (50.00%) 108 (100.0%)
Conclusion:
Higher PD-L1 expression is associated with solid pattern in adenocarcinoma and higher level of tumoral immune infiltrate. We developed an immune score which when combined with PD-L1 expression significantly correlates with patient outcome in surgically resected ADCs. (Supported by grants UT-Lung SPORE P50CA70907 and CPRIT RP120713).
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P3.03 - Poster Session/ Treatment of Locoregional Disease – NSCLC (ID 214)
- Event: WCLC 2015
- Type: Poster
- Track: Treatment of Locoregional Disease – NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P3.03-032 - MD Anderson Oncology Expert Advisor™: A Cognitive Clinical Decision Support Tool for Evidence-Based Multi-Disciplinary Lung Cancer Care (ID 3039)
09:30 - 17:00 | Author(s): J.V. Heymach
- Abstract
Background:
The majority of patients diagnosed with non-small cell lung cancer (NSCLC) receive care in the community setting with limited access to multidisciplinary management common in tertiary care centers. The availability of genomics allows tailored treatments for patients; and with novel, rapidly emerging therapeutic options, it is challenging for busy clinicians to maintain familiarity with current therapy recommendations. Therefore, to empower practicing oncologists in community settings to offer the optimal management at the first intervention, we have developed the MD Anderson Oncology Expert Advisor™ (OEA) application for multi-disciplinary management of lung cancer patients. As the first multi-disciplinary solution for providing comprehensive management of lung cancer, the objective of OEA™ Lung is to leverage cognitive analytics on vast and ever evolving clinical care information and patient big data to disseminate knowledge and expertise, thus enabling physicians to provide evidence-based care and management tailored for the individual patient, similar to consulting an expert. Further, we aimed to create a system for sharing knowledge from more experienced experts to provide care pathways and management recommendations for physicians globally.
Methods:
Using cognitive computing, our cancer center partnered with IBM Watson to develop an expert system designed to provide physicians with the tools needed to process high-volume patient and medical information and to stay up-to-date with the latest treatment and management options, so that they can make the best evidence-based treatment decisions for their lung cancer patients. The OEA™ application for lung was built upon core capabilities of the OEA™ applications for leukemia and molecular/targeted therapies. Experts in multiple disciplines including thoracic surgery, medical oncology, and radiation oncology met regularly to design and provide specialized input to the IBM technical team in an agile development cycle. This system was powered to utilize both structured and unstructured data from validated sources; to thoroughly evaluate and stage patients; and to offer eligible clinical trials and personalized therapeutic options. In addition to delivering evidence-based, weighted therapy recommendations, OEA™ Lung provides care pathways for management of toxicities for each treatment modality (surgery, radiation, and medical oncology).
Results:
The OEA™ Lung application supports three core functions: 1) dynamic patient summary assimilating complete (structured and unstructured) data to show demographics, labs, genotype, treatment history, and previous treatment responses; 2) weighted evidence-based, multimodality treatment options, with recommendations based on literature support which is provided, along with screening for relevant trials; 3) care pathway advisories, to manage treatment related toxicities for each modality. Further, this product improves quality of care by optimizing outcomes with access to trials and care pathways.
Conclusion:
The OEA™ application for lung is a cognitive expert system designed to assimilate multidisciplinary recommendations for care and management of lung cancer patients based on current consensus guidelines and expert recommendations from a quaternary referral cancer center to the community practice setting. By democratizing knowledge from our specialty cancer center, we have taken steps toward achieving an important goal of ending cancer for all, by providing global access to optimal cancer care for patients with this disease. Further evaluation of outcomes following implementation are warranted.
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P3.04 - Poster Session/ Biology, Pathology, and Molecular Testing (ID 235)
- Event: WCLC 2015
- Type: Poster
- Track: Biology, Pathology, and Molecular Testing
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2015, 09:30 - 17:00, Exhibit Hall (Hall B+C)
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P3.04-031 - Combining CT Texture Analysis with Semantic Imaging Descriptions for the Radiogenomic Detection of EGFR and KRAS Mutations in NSCLC (ID 2965)
09:30 - 17:00 | Author(s): J.V. Heymach
- Abstract
Background:
Existing literature suggests quantitative texture features derived from CT imaging can differentiate tumor genotypes and phenotypes. We combined CT texture analysis with semantic imaging descriptions provided by radiologists, and evaluated their ability to identify EGFR and KRAS mutation status in NSCLC.
Methods:
We retrospectively reviewed CT images from 628 patients from the GEMINI (Genomic Marker-Guided Therapy Initiative) cohort. Included were NSCLC patients whose biopsies included genetic testing for EGFR or KRAS mutations, and who underwent contrast-enhanced CT imaging within 90 days of biopsy. Excluded were patients who had undergone therapy or biopsy of their primary tumor before imaging, or whose tumors weren’t segmentable. All CT images were contrast-enhanced, with body kernel reconstruction, and slice thicknesses of 1.25-5mm. Tumor segmentation was done in 3DSlicer (Harvard University, Cambridge MA) using a semi-automatic segmentation algorithm. Image pre-processing and textural feature extraction was performed using IBEX (MDACC, Houston TX). Semantic descriptions of the tumors were recorded by a thoracic radiology fellow and a board-certified thoracic radiologist in consensus. For each patient a set of textural features was calculated, based on the GreyLevel Co-Occurrence Matrix, Run-Length Matrix, voxel intensity histogram, and geometric properties of the tumor. Feature selection was based on existing literature, prior research experience, and excluded those features previously found to be poorly reproducible in lung tissue. These were combined with semantic descriptions (e.g. presence or absence of features such as spiculations, air bronchograms, and pleural effusions), for a total of 51 textural and geometric features, and 11 semantic features. When available, the SUVmax for the tumor was also included. To detect correlations with genetic mutations, these features were combined to train a Random Forest machine learning algorithm. This algorithm output a prediction for the mutation status of each tumor, and the predictive accuracy was assessed based on 10-fold cross-validation.
Results:
Included were 121 patients, 113 tested for KRAS mutations (26 positive) and 118 tested for EGFR mutations (31 positive). Maximum tumor dimensions ranged from 1.2–15.5cm (mean 5.6cm). Individual semantic features found to correlate with mutation status included tumor cavitation, pleural effusion, presence of ground glass opacity, and the nature of tumor margins (all p-values <0.05). Used collectively in a Random Forest classifier, textural features alone showed a sensitivity and specificity for KRAS detection of 50% and 81% respectively, with 74% overall accuracy. This increased modestly to a sensitivity and specificity of 50% and 84% respectively when semantic features were added, with accuracy increasing to 77%. For EGFR detection, textural features had sensitivity and specificity of 48% and 77% respectively, giving 69% accuracy. Detection of EGFR did not improve with inclusion of semantic features.
Conclusion:
Texture analysis correctly identified EGFR and KRAS mutation status in most patients. Although some semantic features correlated with mutation status, when combined with textural features they provided little or no improvement in predictive accuracy. One possible explanation is that textural features may already be capturing the information contained in the semantic features. Our results suggest oncogenic drivers of NSCLC are associated with distinct imaging features that can be detected radiographically.
