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Brief Report

Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer

by
Shelley Kuang
1,†,
Andrea S. Fung
1,†,
Kirstin A. Perdrizet
1,†,
Kaitlin Chen
1,
Janice J. N. Li
1,
Lisa W. Le
2,
Michael Cabanero
3,
Ola Abu Al Karsaneh
3,4,
Ming S. Tsao
3,
Josh Morganstein
3,
Laura Ranich
3,
Adam C. Smith
3,
Cuihong Wei
3,
Carol Cheung
3,
Frances A. Shepherd
1,
Geoffrey Liu
1,
Penelope Bradbury
1,
Prodipto Pal
3,
Joerg Schwock
3,
Adrian G. Sacher
1,
Jennifer H. Law
1,
Tracy L. Stockley
3,‡ and
Natasha B. Leighl
1,*,‡
add Show full author list remove Hide full author list
1
Department of Medical Oncology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2M9, Canada
2
Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2M9, Canada
3
Department of Laboratory Medicine & Pathology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G 2M9, Canada
4
Department of Basic Medical Sciences, Faculty of Medicine, The Hashemite University, Zarqa 13133, Jordan
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
T.L.S. and N.B.L. are co-principal investigators.
Curr. Oncol. 2022, 29(7), 4428-4437; https://doi.org/10.3390/curroncol29070352
Submission received: 14 May 2022 / Revised: 17 June 2022 / Accepted: 20 June 2022 / Published: 22 June 2022
(This article belongs to the Section Thoracic Oncology)

Abstract

:
In advanced non-small cell lung cancer (NSCLC), patients with actionable genomic alterations may derive additional clinical benefit from targeted treatment compared to cytotoxic chemotherapy. Current guidelines recommend extensive testing with next generation sequencing (NGS) panels. We investigated the impact of using a targeted NGS panel (TruSight Tumor 15, Illumina) as reflex testing for NSCLC samples at a single institution. Molecular analysis examined 15 genes for hotspot mutation variants, including AKT1, BRAF, EGFR, ERBB2, FOXL2, GNA11, GNAQ, KIT, KRAS, MET, NRAS, PDGFRA, PIK3CA, RET and TP53 genes. Between February 2017 and October 2020, 1460 samples from 1395 patients were analyzed. 1201 patients (86.1%) had at least one variant identified, most frequently TP53 (47.5%), KRAS (32.2%) or EGFR (24.2%). Among these, 994 patients (71.3%) had clinically relevant variants eligible for treatment with approved therapies or clinical trial enrollment. The incremental cost of NGS beyond single gene testing (EGFR, ALK) was CAD $233 per case. Reflex upfront NGS identified at least one actionable variant in more than 70% of patients with NSCLC, with minimal increase in testing cost. Implementation of NGS panels remains essential as treatment paradigms continue to evolve.

1. Introduction

In advanced non-small cell lung cancer (NSCLC), novel targeted treatment options continue to emerge as more oncogenic driver alterations are identified. Updated guidelines from the American Society of Clinical Oncology-Ontario Health (ASCO-OH), National Comprehensive Cancer Network (NCCN), International Association for the Study of Lung Cancer/College of American Pathology (IASLC/CAP) and European Society of Medical Oncology (ESMO) all recommend extensive testing with next generation sequencing (NGS) platforms to identify actionable alterations in EGFR, ALK, ROS1, BRAF, HER2, KRAS, MET, NTRK and RET, as well as immunochemistry for PD-L1 [1,2,3,4].
If actionable genomic alterations are identified, patients may gain access to targeted treatment options, which can improve patient outcomes including response, quality of life, progression-free survival and potentially overall survival compared to cytotoxic chemotherapy. Thus, the implementation of broader NGS platforms has become essential in the routine diagnosis and management of NSCLC patients. In managed care systems, assessment of the costs of broader testing and impact on patient care are also needed.
We investigated the impact of using a targeted NGS 15-gene panel (TruSight Tumor 15 [TST15], Illumina, San Diego, CA, USA) as part of the routine reflex testing for non-squamous NSCLC samples at a single institution.

2. Materials and Methods

The conduct of this prospective study was approved by the University Health Network (UHN) Research Ethics Board. Between February 2017 and October 2020, the UHN Genome Diagnostics Laboratory used the TST15 gene panel to test diagnostic samples of non-squamous NSCLC tumor tissue with reflex ordering by UHN pathologists, or as requested by the patient’s medical oncologist. Formalin fixed, paraffin embedded (FFPE) tumor samples were assessed for sufficiency and tumor rich areas identified by a board-certified pathologist, with a minimum tumor tissue surface area of 10 mm2 and ≥30% nucleated tumor cells required. DNA was extracted from macrodissected FFPE tissue. Molecular analysis used 20 ng DNA with a commercially available NGS targeted panel (TruSight Tumor 15, TST15, Illumina) sequenced on the MiSeq platform (2 × 150 bp configuration, Illumina). The TST15 includes regions of 15 genes covering hotspot variants, including single nucleotide variants and small insertions/deletions in the AKT1, BRAF, EGFR, ERBB2, FOXL2, GNA11, GNAQ, KIT, KRAS, MET, NRAS, PDGFRA, PIK3CA, RET and TP53 genes. Bioinformatic analysis used MiSeq Reporter with manufacturer supplied TST analysis module (Illumina). Variants were classified according to Sukhai et al. [5]. In addition, samples underwent reflex testing for ALK gene fusions (5A4 IHC), PD-L1 (22C3 IHC pharmDx Assay) and in 2020, screening for ROS1 fusions was initiated using IHC (D4D6 antibody) with FISH confirmation of positive cases [6,7,8].
Baseline demographic and treatment data were recorded prospectively including age, sex, smoking status, stage at diagnosis and pathologic subtype. For each specimen tested, the type of sample and site of origin were identified. Turnaround time (TAT) for profiling results was calculated from date of sample collection to report of genomic results to the oncologist, which included sample processing (formalin fixation and paraffin embedding), pathology review, clinical scientist review and final pathology sign-out. Molecular testing data were recorded based on the TST15 results as well as immunohistochemistry results for ALK, ROS1 and PD-L1 expression. For patients who had multiple tumours tested, synchronous tumours were defined by repeat testing within 6 months, and metachronous tumours if testing was repeated more than 6 months later. Treatment and outcomes were collected manually and with automated natural language processing (DarwenTM), previously validated and shown to be highly accurate [9].
Actionable alterations were defined as variants which could be targetable using approved or active investigational therapies. Clinical trial eligibility was determined by the presence of interventional studies in NSCLC patients for the variant of interest, using ClinicalTrials.gov (see Data S1 for search terms). Incremental testing costs were calculated based on direct laboratory costs, including reagents, informatics, annotation, and technical time, but excluded overhead and administrative costs. Government reimbursement for single gene testing was subtracted. It was assumed that pathologist and pathology technician costs were similar whether TST15 or single gene (EGFR, EGFR-RT52, Entrogen, Woodland Hills, CA, USA) testing was used, as the pathology activities were not different for these tests.

3. Results

Between February 2017 and October 2020, 1460 samples from 1395 patients were analyzed, with another 24 patient samples excluded due to non-lung cancer diagnosis or loss to follow up (Figure 1).
Baseline characteristics of patients and samples are listed in Table 1 and Table 2, respectively.
The median age of patients was 68.6 years, 52.3% were female, 33.1% were lifetime never smokers, and 85.9% had adenocarcinoma. Of the 1460 samples analyzed, 68.3% of samples were obtained from the lung cancer primary site; 45.5% of samples tested were from core biopsies. The mean turnaround time for reflex profiling results was 28.9 days (SD 8.9).
Of 1395 patients, 1201 patients (86.1%) had at least one variant identified in their cancer sample using TST15, while 405 (29.0%) had two or more co-mutations identified. The most frequently identified variants were in TP53 (47.5%), followed by KRAS (32.2%) and EGFR (24.2%) (Table 3, full list in Data S2). Immunohistochemistry testing also identified 49 patients (4.1%) with tumor ALK fusions among 1202 patients who underwent testing, and 16 patients (1.1%) had ROS1 rearrangements confirmed by FISH. PD-L1 TPS results were ≥50% for 337 patients (24.2%), 1–49% for 374 (26.8%) and negative (<1%) for 515 (36.9%). PD-L1 expression was unknown or testing inconclusive for 169 patients (12.1%).
Although most patients had single tumor sample sent for TST15 testing, 53 patients (3.8%) had multiple samples tested. Among these, 38 patients had synchronous samples tested and results were discordant for 20 (53%). For the 15 patients with metachronous tumor samples tested, 11 (73%) had discordant results.
When assessed based on smoking status, 444 patients were identified as never smokers, and 897 patients were former or current smokers. Among those who were never smokers, the most frequently exhibited variants were in EGFR (51.4%) and TP53 (37.8%), while in previous and current smokers, variants in TP53 (52.3%) and KRAS (43.8%) were more prevalent (Table 3).
When stratified by age, patients over and under 65 years of age demonstrated a similar frequency of tumor variants (Table 4).
The most common co-mutations identified were in KRAS/TP53 (163, 40.2%), followed by EGFR/TP53 (145, 35.8%), ERBB2/TP53 (17, 4.2%) and BRAF/TP53 (9, 2.2%) (Figure 2).
Using TST15, clinically relevant variants were identified for 994 patients (71.3%), including 200 (14.3%) with Health Canada approved therapies, 870 (62.4%) for clinical trial enrolment (www.clinicaltrials.gov, accessed on 13 May 2022), and 30 (2.2%) for off-label treatments (e.g., afatinib or TDM-1 for ERBB2 variants) (Figure 3).
The incremental cost of TST15 beyond reimbursed single gene testing for EGFR and ALK was CAD $233 per case.
In patients with advanced NSCLC, 203 received targeted therapy during their treatment course. Among them, 80 patients received 2 or more lines of targeted treatment for variants in ERBB2, EGFR (classic and exon 20 insertions), KRAS G12C and MET, as well as for ALK and ROS1 rearrangements.

4. Discussion

Reflex upfront next generation sequencing with a 15-gene panel identified at least one variant in more than 80% of tested samples among patients with newly diagnosed non-small cell lung cancer. Of these, 71% derived incremental gain from testing by obtaining access to targeted therapy or becoming eligible for clinical trials based on genomic results, with only a minimal increase in testing costs (CAD $233 per case).
Advances in targeted therapies have led to updated NSCLC treatment guidelines across many gene variants. In metastatic NSCLC, treatment with targeted therapy may result in improved response rate, quality of life, progression-free and overall survival compared to cytotoxic chemotherapy in the first and subsequent line settings. In early stage NSCLC, the role of targeted therapy in the adjuvant setting continues to be explored in clinical trials. In addition to its therapeutic implications, the identification of oncogenic variants also provides valuable prognostic and predictive information [10].
EGFR variants were identified in 50% of never smokers and 10% of former and current smokers, consistent with its incidence in previously reported studies [11]. In contrast, KRAS variants were present in 43% of former and current smokers, which may be slightly higher than prior reports of 25–35% [12]. This could be related to the improved rate of variant detection using TST15 compared to previous methods of sequencing, as demonstrated in its validation study [13].
Although prior literature has described increased rate of molecular alterations in patients under 40 years old, this was not appreciated in this study, given the small sample size of patients within this age group [14]. Patients between the ages of 41–65 and over 65 had similar frequency of alterations.
For patients who had multiple samples tested, 53% of synchronous samples tested had discordant results, compared to 73% of metachronous samples tested. The reasons for this rate of discordance are unclear, and may be related to sampling heterogeneity and potentially increased diversity in later stages of tumor progression, related to the evolution of subclones [15].
One limitation of the NGS testing in our study was the turnaround time between sample collection and report of results, with a mean of 29 days. This time included multiple steps in the process, including sample pathology processing (formalin fixation and paraffin embedding), pathology review, laboratory NGS testing, clinical scientist review and final pathology sign-out. In addition, the TST15 panel was run in batches for cost reasons. However, current Ontario provincial guidelines recommend that NGS testing be completed within 14 days of sample collection, indicating that there is a need for more resources dedicated to improving TAT [16].
However, even the proposed turnaround times may still be too long for some patients. We have shown previously that only 21% of patients have molecular testing results available at the time of initial medical oncology consultation. Furthermore, delayed results led to delayed initiation of treatment, and 19% of patients eligible for targeted therapy received chemotherapy instead [17]. This would have implications for patients with high PD-L1 expression, who are at risk of starting immunotherapy instead of targeted therapy if genomic results are unavailable, recognizing that checkpoint inhibitor monotherapy in prior studies has been less effective in patients with oncogenic driver alterations. If these patients were switched to targeted therapy in the future, this may also increase their risk of important treatment-related adverse events, such as pneumonitis and hepatitis [18].
Sample quantity and quality remain key issues for successful testing [19,20,21], and NGS can provide a simultaneous result on multiple genes, thus avoiding use of tissue in multiple sequential tests. However, in cases where tissue is very small, immunohistochemistry remains an important modality in rapid assessment of ALK and ROS1 rearrangements and PD-L1 expression in patients with NSCLC [6,7,8,22]. IHC may also be advantageous over NGS in cases when a shorter turnaround time is required, and for the detection of fusion genes such as NTRK. The identification of oncogenic protein expression through IHC may also be predictive for response to targeted therapy [23].
While the use of NGS rapidly expands the population eligible for targeted therapy, many patients may have challenges in accessing these novel agents due to high cost, particularly those in publicly funded systems or without private drug insurance [24]. As diagnostic and therapeutic advancements continue in the field of thoracic oncology, identification of genomic alterations is pivotal in our ability to gain access to novel therapies that improve patient and system outcomes. Current guidelines recommend comprehensive assessment of multiple variant types, including single nucleotide variants, small insertions/deletions, fusions and copy number variations [25]. Given the impact on clinical outcomes, development of comprehensive and affordable NGS panels is essential as standard of care molecular testing requirements continue to evolve.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/curroncol29070352/s1, Data S1. Search terms used on ClinicalTrials.gov; Data S2. Variants detected using TST15.

Author Contributions

Conceptualization, K.A.P., T.L.S. and N.B.L.; formal analysis, S.K., A.S.F., K.A.P., L.W.L., N.B.L.; data curation, S.K., A.S.F., K.A.P., K.C., J.J.N.L., M.C., O.A.A.K., M.S.T., J.M., L.R., A.C.S., C.W., C.C., F.A.S., G.L., P.B., P.P., J.S., A.G.S., J.H.L., T.L.S., N.B.L.; writing—original draft preparation, S.K., A.S.F., K.A.P., N.B.L.; writing—review and editing, K.C., J.J.N.L., M.C., O.A.A.K., M.S.T., J.M., L.R., A.C.S., C.W., C.C., F.A.S., G.L., P.B., P.P., J.S., A.G.S., J.H.L., T.L.S.; All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Princess Margaret Cancer Foundation (OSI Pharmaceuticals Foundation Chair; Silstar Foundation).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Research Ethics Board of University Health Network.

Informed Consent Statement

Patient consent was waived due to the retrospective nature of the study.

Data Availability Statement

The data presented in this study is available in this article (and supplementary material).

Acknowledgments

The authors gratefully acknowledge support from the PM Cancer Foundation, Silstar Foundation, UHN Genome Diagnostics Laboratory and the UHN Laboratory Medicine Program. We thank Christopher Penttengell and the Pentavere Research Group for their funding support for data collection.

Conflicts of Interest

The authors declare no conflict of interest relevant to this study.

References

  1. National Comprehensive Cancer Network. Non-Small Cell Lung Cancer. Version 3.2022. 16 March 2022. Available online: https://www.nccn.org/login?ReturnURL=https://www.nccn.org/professionals/physician_gls/pdf/nscl.pdf (accessed on 13 May 2022).
  2. Kalemkerian, G.P.; Narula, N.; Kennedy, E.B.; Biermann, W.A.; Donington, J.; Leighl, N.B.; Lew, M.; Pantelas, J.; Ramalingam, S.S.; Reck, M.; et al. Molecular Testing Guideline for the Selection of Patients with Lung Cancer for Treatment With Targeted Tyrosine Kinase Inhibitors: American Society of Clinical Oncology Endorsement of the College of American Pathologists/International Association for the Study of Lung Cancer/Association for Molecular Pathology Clinical Practice Guideline Update. J. Clin. Oncol. 2018, 36, 911–919. [Google Scholar] [CrossRef] [PubMed]
  3. Lindeman, N.I.; Cagle, P.T.; Aisner, D.L.; Arcila, M.E.; Beasley, M.B.; Bernicker, E.H.; Colasacco, C.; Dacic, S.; Hirsch, F.R.; Kerr, K.; et al. Updated Molecular Testing Guideline for the Selection of Lung Cancer Patients for Treatment with Targeted Tyrosine Kinase Inhibitors: Guideline From the College of American Pathologists, the International Association for the Study of Lung Cancer, and the Association for Molecular Pathology. Arch. Pathol. Lab. Med. 2018, 142, 321–346. [Google Scholar] [CrossRef] [Green Version]
  4. Planchard, D.; Popat, S.; Kerr, K.; Novello, S.; Smit, E.F.; Faivre-Finn, C.; Mok, T.S.; Reck, M.; Van Schil, P.E.; Hellmann, M.D.; et al. Metastatic non-small cell lung cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2018, 29 (Suppl. 4), iv192–iv237. [Google Scholar] [CrossRef] [PubMed]
  5. Sukhai, M.A.; Craddock, K.J.; Thomas, M.; Hansen, A.R.; Zhang, T.; Siu, L.; Bedard, P.; Stockley, T.L.; Kamel-Reid, S. A classification system for clinical relevance of somatic variants identified in molecular profiling of cancer. Genet. Med. 2016, 18, 128–136. [Google Scholar] [CrossRef] [Green Version]
  6. Fiset, P.O.; Labbé, C.; Young, K.; Craddock, K.J.; Smith, A.C.; Tanguay, J.; Pintilie, M.; Wang, R.; Torlakovic, E.; Cheung, C.; et al. Anaplastic lymphoma kinase 5A4 immunohistochemistry as a diagnostic assay in lung cancer: A Canadian reference testing center’s results in population-based reflex testing. Cancer 2019, 125, 4043–4051. [Google Scholar] [CrossRef]
  7. Hwang, D.M.; Albaqer, T.; Santiago, R.C.; Weiss, J.; Tanguay, J.; Cabanero, M.; Leung, Y.; Pal, P.; Khan, Z.; Lau, S.C.M.; et al. Prevalence and Heterogeneity of PD-L1 Expression by 22C3 Assay in Routine Population-Based and Reflexive Clinical Testing in Lung Cancer. J. Thorac. Oncol. 2021, 16, 1490–1500. [Google Scholar] [CrossRef]
  8. Cheung, C.C.; Smith, A.C.; Albadine, R.; Bigras, G.; Bojarski, A.; Couture, C.; Cutz, J.C.; Huang, W.Y.; Ionescu, D.; Itani, D.; et al. Canadian ROS proto-oncogene 1 study (CROS) for multi-institutional implementation of ROS1 testing in non-small cell lung cancer. Lung Cancer 2021, 160, 127–135. [Google Scholar] [CrossRef]
  9. Gauthier, M.; Law, J.; Le, L.; Li, J.J.N.; Zahir, S.; Nirmalakumar, S.; Sung, M.; Pettengell, C.; Aviv, S.; Chu, R.; et al. Automating Access to Real-World Evidence. J. Thorac. Oncol. 2022, 3, 100340. [Google Scholar] [CrossRef]
  10. Yuan, M.; Huang, L.L.; Chen, J.H.; Wu, J.; Xu, Q. The emerging treatment landscape of targeted therapy in non-small-cell lung cancer. Signal. Transduct. Target Ther. 2019, 4, 61. [Google Scholar] [CrossRef] [Green Version]
  11. Rivera, G.A.; Wakelee, H. Lung Cancer in Never Smokers. Adv. Exp. Med. Biol. 2016, 893, 43–57. [Google Scholar] [CrossRef]
  12. Kempf, E.; Rousseau, B.; Besse, B.; Paz-Ares, L. KRAS oncogene in lung cancer: Focus on molecularly driven clinical trials. Eur. Respir. Rev. 2016, 25, 71–76. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Illumina, I. Multi-Site Analytical Validation of TruSight® Tumor 15 (TST15) Determining Robustness and Concordance. 2022. Available online: https://www.illumina.com/products/by-type/clinical-research-products/trusight-tumor-15-gene.html (accessed on 8 April 2022).
  14. Catania, C.; Botteri, E.; Barberis, M.; Conforti, F.; Toffalorio, F.; De Marinis, F.; Boselli, S.; Noberasco, C.; Delmonte, A.; Spitaleri, G.; et al. Molecular features and clinical outcome of lung malignancies in very young people. Future Oncol. 2015, 11, 1211–1221. [Google Scholar] [CrossRef] [PubMed]
  15. Gerstung, M.; Jolly, C.; Leshchiner, I.; Dentro, S.C.; Gonzalez, S.; Rosebrock, D.; Mitchell, T.J.; Rubanova, Y.; Anur, P.; Yu, K.; et al. The evolutionary history of 2,658 cancers. Nature 2020, 578, 122–128. [Google Scholar] [CrossRef] [Green Version]
  16. Lindeman, N.I.; Cagle, P.T.; Beasley, M.B.; Chitale, D.A.; Dacic, S.; Giaccone, G.; Jenkins, R.B.; Kwiatkowski, D.J.; Saldivar, J.S.; Squire, J.; et al. Molecular testing guideline for selection of lung cancer patients for EGFR and ALK tyrosine kinase inhibitors: Guideline from the College of American Pathologists, International Association for the Study of Lung Cancer, and Association for Molecular Pathology. J. Thorac. Oncol. 2013, 8, 823–859. [Google Scholar] [CrossRef] [Green Version]
  17. Lim, C.; Tsao, M.S.; Le, L.W.; Shepherd, F.A.; Feld, R.; Burkes, R.L.; Liu, G.; Kamel-Reid, S.; Hwang, D.; Tanguay, J.; et al. Biomarker testing and time to treatment decision in patients with advanced nonsmall-cell lung cancer. Ann. Oncol. 2015, 26, 1415–1421. [Google Scholar] [CrossRef] [PubMed]
  18. Schoenfeld, A.J.; Arbour, K.C.; Rizvi, H.; Iqbal, A.N.; Gadgeel, S.M.; Girshman, J.; Kris, M.G.; Riely, G.J.; Yu, H.A.; Hellmann, M.D. Severe immune-related adverse events are common with sequential PD-(L)1 blockade and osimertinib. Ann. Oncol. 2019, 30, 839–844. [Google Scholar] [CrossRef]
  19. Shiau, C.J.; Babwah, J.P.; da Cunha Santos, G.; Sykes, J.R.; Boerner, S.L.; Geddie, W.R.; Leighl, N.B.; Wei, C.; Kamel-Reid, S.; Hwang, D.M.; et al. Sample features associated with success rates in population-based EGFR mutation testing. J. Thorac. Oncol. 2014, 9, 947–956. [Google Scholar] [CrossRef] [Green Version]
  20. Lim, C.; Sekhon, H.S.; Cutz, J.C.; Hwang, D.M.; Kamel-Reid, S.; Carter, R.F.; Santos, G.D.C.; Waddell, T.; Binnie, M.; Patel, M.; et al. Improving molecular testing and personalized medicine in non-small-cell lung cancer in Ontario. Curr. Oncol. 2017, 24, 103–110. [Google Scholar] [CrossRef] [Green Version]
  21. Zer, A.; Cutz, J.C.; Sekhon, H.; Hwang, D.M.; Sit, C.; Maganti, M.; Sung, M.; Binnie, M.; Brade, A.; Chung, T.B.; et al. Translation of Knowledge to Practice-Improving Awareness in NSCLC Molecular Testing. J. Thorac. Oncol. 2018, 13, 1004–1011. [Google Scholar] [CrossRef] [Green Version]
  22. Makarem, M.; Ezeife, D.A.; Smith, A.C.; Li, J.J.N.; Law, J.H.; Tsao, M.S.; Leighl, N.B. Reflex ROS1 IHC Screening with FISH Confirmation for Advanced Non-Small Cell Lung Cancer-A Cost-Efficient Strategy in a Public Healthcare System. Curr. Oncol. 2021, 28, 3268–3279. [Google Scholar] [CrossRef]
  23. Tsao, M.S.; Yatabe, Y. Old Soldiers Never Die: Is There Still a Role for Immunohistochemistry in the Era of Next-Generation Sequencing Panel Testing? J. Thorac. Oncol. 2019, 14, 2035–2038. [Google Scholar] [CrossRef] [PubMed]
  24. Leighl, N.B.; Nirmalakumar, S.; Ezeife, D.A.; Gyawali, B. An Arm and a Leg: The Rising Cost of Cancer Drugs and Impact on Access. Am. Soc. Clin. Oncol. Educ. Book 2021, 41, e1–e12. [Google Scholar] [CrossRef] [PubMed]
  25. Perdrizet, K.; Stockley, T.; Law, J.; Smith, A.; Zhang, T.; Fernandes, R.; Shabir, M.; Sabatini, P.; Youssef, N.; Ishu, C.; et al. Integrating comprehensive genomic sequencing of non-small cell lung cancer into a public healthcare system. Cancer Treat. Res. Commun. 2022, 31, 100534. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Study flow diagram.
Figure 1. Study flow diagram.
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Figure 2. Genomic co-alterations identified (N = 1395 patients).
Figure 2. Genomic co-alterations identified (N = 1395 patients).
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Figure 3. Incremental clinical benefit from use of 15-gene panel versus single gene testing.
Figure 3. Incremental clinical benefit from use of 15-gene panel versus single gene testing.
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Table 1. Patient and disease characteristics (N = 1395 patients).
Table 1. Patient and disease characteristics (N = 1395 patients).
Number (%)
N = 1395
Age at diagnosis, median (range)68.6 years (18.8–97.2)
Sex
  Female730 (52.3%)
  Male665 (47.7%)
Smoking status
  Never444 (33.1%)
  Former Smoker492 (36.7%)
  Current Smoker405 (30.2%)
  Unknown54
Stage at diagnosis
  I485 (35.0%)
  II109 (7.9%)
  III231 (16.7%)
  IV560 (40.4%)
  Unknown10
Histology
  Adenocarcinoma1198 (85.9%)
  Large Cell40 (2.9%)
  Squamous34 (2.4%)
  Pleomorphic/Sarcomatoid14 (1.0%)
  Small Cell12 (0.9%)
  Mixed histology6 (1.2%)
  Not otherwise specified91 (6.5%)
Table 2. Sample characteristics (N = 1460 samples).
Table 2. Sample characteristics (N = 1460 samples).
Number (%)
N = 1460
Samples tested per patient *
   11335 (95.7%)
   255 (3.9%)
   35 (0.4%)
Sample type
   Core biopsy665 (45.5%)
   Surgical specimen379 (26.0%)
   FNA cytology353 (24.2%)
   Exfoliative cytology62 (4.2%)
   Unknown1
Sample site
  Primary (lung)997 (68.3%)
  Non-bone visceral or soft tissue metastasis357 (24.5%)
  Pleural fluid57 (3.9%)
  Bone metastasis33 (2.3%)
  Other16 (1.1%)
* 7 of 60 patients with multiple samples tested had unsuccessful profiling of at least one sample.
Table 3. Molecular results based on smoking status.
Table 3. Molecular results based on smoking status.
Gene VariantNever Smoker (N = 444)Former/Current Smoker (N = 897)All Patients (N = 1395)
AKT03 (0.3%)3 (0.2%)
BRAF7 (1.6%)21 (2.3%)29 (2.1%)
  V600E *61118
  Non-V600E11011
EGFR228 (51.4%)97 (10.8%)337 (24.2%)
  Exon 19 deletion *10241147
  L858R *9834137
  Other Exon 19/20/21121227
  Exon 18 *131024
  Exon 20 insertion *17118
  T790M *111516
  L861Q *5510
  C797S101
  ≥2 EGFR variants281140
ERBB220 (4.5%)10 (1.1%)30 (2.2%)
  Exon 2017522
  Transmembrane domain224
  Other134
KRAS40 (9.0%)393 (43.8%)449 (32.2%)
  G12C *4152161
  Non-G12C36253300
  ≥2 KRAS variants01212
MET1 (0.1%)3 (0.3%)4 (0.3%)
  Exon 14 splice site *112
  Exon 14 skipping *011
  Non-splice site missense011
NRAS1 (0.1%)2 (0.2%)3 (0.2%)
PI3KCA15 (3.4%)29 (3.2%)45 (3.2%)
RET *02 (0.2%)2 (0.1%)
TP53168 (37.8%)469 (52.3%)662 (47.5%)
* Actionable alterations with approved targeted therapy.
Table 4. Molecular results by patient age.
Table 4. Molecular results by patient age.
Gene Variant<40 years
(N = 19)
40-65 years
(N = 506)
≥65 years
(N = 870)
AKT01 (0.2%)2 (0.2%)
BRAF06 (1.2%)23 (2.6%)
  V600E *0513
  Non-V600E0110
EGFR2 (10.5%)132 (26.1%)203 (23.3%)
  Exon 19 deletion *06879
  L858R *14888
  Other Exon 19/20/2101017
  Exon 18 *1716
  Exon 20 insertion *0711
  T790M *088
  L861Q *028
  C797S010
  ≥2 EGFR variants01723
ERBB21 (5.3%)14 (2.8%)15 (1.7%)
  Exon 201912
  Transmembrane domain022
  Other031
KRAS1 (5.3%)153 (30.2%)295 (33.9%)
  G12C *055106
  Non-G12C1102197
  ≥2 KRAS variants048
MET004 (0.5%)
  Exon 14 splice site *002
  Exon 14 skipping *001
  Non-splice site missense001
NRAS003 (0.3%)
PI3KCA013 (2.6%)32 (3.7%)
RET *02 (0.4%)0
TP539 (47.4%)251 (49.6%)402 (46.2%)
* Actionable alterations with approved targeted therapy.
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Kuang, S.; Fung, A.S.; Perdrizet, K.A.; Chen, K.; Li, J.J.N.; Le, L.W.; Cabanero, M.; Karsaneh, O.A.A.; Tsao, M.S.; Morganstein, J.; et al. Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer. Curr. Oncol. 2022, 29, 4428-4437. https://doi.org/10.3390/curroncol29070352

AMA Style

Kuang S, Fung AS, Perdrizet KA, Chen K, Li JJN, Le LW, Cabanero M, Karsaneh OAA, Tsao MS, Morganstein J, et al. Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer. Current Oncology. 2022; 29(7):4428-4437. https://doi.org/10.3390/curroncol29070352

Chicago/Turabian Style

Kuang, Shelley, Andrea S. Fung, Kirstin A. Perdrizet, Kaitlin Chen, Janice J. N. Li, Lisa W. Le, Michael Cabanero, Ola Abu Al Karsaneh, Ming S. Tsao, Josh Morganstein, and et al. 2022. "Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer" Current Oncology 29, no. 7: 4428-4437. https://doi.org/10.3390/curroncol29070352

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