Circulating tumor cells as a liquid biopsy in small cell lung cancer, a future editorial

Circulating tumor cells (CTCs)

CTCs are shed tumor cells that have entered the bloodstream and are able to survive in the blood environment often by endothelial mesenchymal transition (EMT) (1-4). It is thought that CTCs mirror tumor heterogeneity of both the primary tumor and metastases, making them an excellent candidate that reflects the behavior of cancer. CTCs may replace invasive biopsies of the original tumor as a diagnostic tool, lowering the diagnostic burden placed on patients. Follow-up of number of CTCs will give physicians the opportunity to monitor therapy efficacy and observe relapses in time. A major prerequisite is that enough CTCs are being detected; in small cell lung cancer (SCLC) a variable amount of about 20 to 20,000 CTCs are found in 7.5 mL blood.

CTCs numbers in SCLC

Hou et al. showed that CTCs are prognostic for survival in SCLC patients, and observed decreasing CTCs after therapy in responding patients (5). These findings were confirmed in 2012 (6). Hiltermann et al. showed that a decrease in CTC counts after the first course of therapy already predicted tumor response (7). Similar findings were found in other studies (8-10). CTC enumeration is therefore a very promising biomarker for chemotherapy efficacy. Molecular characterization of CTCs may help us to understand mechanisms of metastasis and resistance, hopefully leading to better treatments in this disease where chemotherapy and radiation are still the only known effective treatments (11).

CTCs and copy number variation (CNV) or aberration status

SCLC has a very high mutation rate, as shown by Peifer et al. when by sequencing 29 SCLC exomes, 2 genomes and 15 transcriptomes of SCLC tumors, they observed 7.4±1 protein-changing mutations per million base pairs (12).

In 2013 Ni et al. described CNV patterns in CTCs of lung cancer patients that are highly reproducible for individual patients (13). Tumor subtyping in adenocarcinoma and SCLC could be made on basis of CTC CNV. These patterns were not affected by drug treatment as described in one SCLC patient. For the 23 genes with significantly increased mutation frequencies in response to chemotherapy, six genes (ALPK2, KIF16B, TP53, MYH7, TTLL2, PAK2) were enriched and possibly involved in resistance. In 2017 Carter et al. were the first to demonstrate the predictive value of copy number aberrations (CNAs) in CTCs in 31 patients with SCLC (14). SCLC patients receiving chemotherapy were classified as either chemorefractory [progressive disease (PD) within 90 days after completion of chemotherapy] or chemosensitive (PD after 90 days). First, 88 baseline CTC samples from 13 patients were used to create a CNA-based classifier by combining CNA status with clinical response to chemotherapy. They studied the known 13 gene signatures with frequently altered genes in SCLC (8 amplified and 5 deleted genes). No segregation between chemosensitive and chemoresistant status was observed, which is in line with the findings of Rudin et al. and Peifer et al. (12,15). Afterwards, the CNA classifier was expanded, and using this new 16 CNA profile classifier the concordance between predicted and clinical outcome (chemosensitive vs. refractory) was 83%. CNV patterns in CTCs were also not influenced by chemotherapy. Initial chemosensitive patients who became chemoresistant had similar CNV patterns in their CTCs. One of the issues is that the CNV test is not sensitive enough and not the right test to detect the many known resistance mechanisms for platinum and etoposide at DNA or protein level.

The 16 CNA profile classifier was subsequently validated in a new set of 18 patients with 112 CTC samples. The classifier correctly assigned 15 out of 18 patients (83.3%) to either the chemosensitive or chemorefractory group. However, the prediction became worse when 1–4 individual CTC calls were in disagreement with the majority of CTCs. This CTC heterogeneity remains an important issue for biomarker studies and therefore a substantial number of single cells are needed to perform robust treatment predictions.

Hurdles in CTC detection

Isolation and detection of CTCs is based on the different physical and biological properties of CTCs compared to normal cells. Different methods to identify and isolate the CTCs (including different definitions of a tumor cell) make comparisons of studies difficult. At this time, the Cell Search system—based on the expression of the epithelial cell adhesion molecule (EpCAM)—is still the only FDA approved system. Other techniques such as the ISET platform (RareCells Inc.) which is based on size and the Clear Cell system (Clearbridge, BioMedics, Singapore) that separates cells by sorted weights are becoming more commonplace, competing with the cell search method (16,17). It is not yet clear how CTCs obtained by different techniques mirror the characteristics of the original tumor and/or its metastases best. Different CTC characteristics should be compared to identify the most important cell traits that determine patient outcome. In the Cell Search system however, identified CTCs are fixed and can’t be used for further cell culturing and molecular characterization of CTCs enclosed in a cartridge after enumeration is a challenge. Another way to isolate CTCs is microsieve filtration where single cells are deposited into microwells (18), from which living tumor cells can be isolated for immunocytochemistry or culturing, which is developed by VyCap (VyCap, Deventer). Another filtration technique from the same company was described by de Wit et al. who used a silicon microsieve on cell waste obtained after Cell Search to detect EpCAM-CTCs on which they carried out FISH (19). The ISET system and the Clear Cell system both offer, after the different methods for filtration or isolation, further characterization of CTCs by molecular analysis, FISH, immunofluorescence or culturing (6,17,20-25). These additional CTC applications will offer more detailed information.

Alternatives to CTCs as liquid biopsy

Currently, circulating tumor DNA (ctDNA), and tumor RNA derived from platelets are other biomarkers to evaluate tumor response and that may be useful for follow-up. Cell free DNA (cfDNA) are nucleic acids detected in body fluids. In cancer patients, at least a part is ctDNA, thought to originate from dying tumor cells. These approaches may be complimentary to CTCs, where high ctDNA and CTC numbers of untreated patients could indicate a high burden of disease.

Fernandez-Cuesta et al. studied ctDNA in SCLC patients, identifying TP53 mutations in ctDNA in the plasma of 53 SCLC patients (49%) and 123 controls (11.4%) (26). This study illustrates that a substantial number of otherwise healthy people showed TP53 mutations without having cancer. This is an important hurdle in the implementation to ctDNA as a screening test. It showed however that it is possible to identify specific mutations in ctDNA, which could be useful in daily practice.

RNA from the tumor is also found in the blood. In 2011 Nilsson et al. showed that tumor RNA was transferred into blood platelets, so called tumor-educated platelets (TEPs) (27). Using TEPs, Best et al. distinguished 228 patients with localized and metastasized tumors from six different origins from 55 healthy individuals with 96% accuracy. They correctly identified the source of the primary tumor with 71% accuracy and they distinguished MET or HER2-positive, and mutant KRAS, EGFR, or PIK3CA tumors (28).

Although both methods have hardly been studied in SCLC, mRNA and ctDNA can be detected in plasma and can be used to detect specific mutations or translocations. CTCs may deliver more information than mere plasma ctDNA or mRNA in platelets. Different cellular surface markers can be stained such as PD-L1, a target for checkpoint inhibitors in lung cancer or delta-like 3 (DLL3), a ligand in the NOTCH signalling pathway that shows increased expression on SCLC tumor cells in biopsies and perhaps also on CTCs. The meaning of CTC expression of these markers has not yet been clarified.

In conclusion, in patients with SCLC, liquid biopsies like CTCs may play a major role to determine tumor biology in a non-invasive way. Standardization and validation of CTCs and cfDNA assays are important issues realized by the current EU/IMI consortium CANCER-ID (www.cancer-id.eu).

Acknowledgments

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned and reviewed by the Section Editor Shaohua Cui (Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tcr.2017.03.69). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Kallergi G, Papadaki MA, Politaki E, et al. Epithelial to mesenchymal transition markers expressed in circulating tumour cells of early and metastatic breast cancer patients. Breast Cancer Res 2011;13:R59. [Crossref] [PubMed]
2. Krebs MG, Metcalf RL, Carter L, et al. Molecular analysis of circulating tumour cells—biology and biomarkers. Nat Rev Clin Oncol 2014;11:129-44. [Crossref] [PubMed]
3. Coumans FAW, Ligthart ST, Uhr JW, et al. Challenges in the enumeration and phenotyping of CTC. Clin Cancer Res 2012;18:5711-8. [Crossref] [PubMed]
4. Zhang C, Guan Y, Sun Y, et al. Tumor heterogeneity and circulating tumor cells. Cancer Lett 2016;374:216-23. [Crossref] [PubMed]
5. Hou JM, Greystoke A, Lancashire L, et al. Evaluation of circulating tumor cells and serological cell death biomarkers in small cell lung cancer patients undergoing chemotherapy. Am J Pathol 2009;175:808-16. [Crossref] [PubMed]
6. Hou JM, Krebs MG, Lancashire L, et al. Clinical significance and molecular characteristics of circulating tumor cells and circulating tumor microemboli in patients with small-cell lung cancer. J Clin Oncol 2012;30:525-32. [Crossref] [PubMed]
7. Hiltermann TJ, Pore MM, van den Berg A, et al. Circulating tumor cells in small-cell lung cancer: A predictive and prognostic factor. Ann Oncol 2012;23:2937-42. [Crossref] [PubMed]
8. Fu L, Liu F, Fu H, et al. Circulating tumor cells correlate with recurrence in stage III small-cell lung cancer after systemic chemoradiotherapy and prophylactic cranial irradiation. Jpn J Clin Oncol 2014;44:948-55. [Crossref] [PubMed]
9. Belani CP, Dahlberg SE, Rudin CM, et al. Vismodegib or cixutumumab in combination with standard chemotherapy for patients with extensive-stage small cell lung cancer: A trial of the ECOG-ACRIN Cancer Research Group (E1508). Cancer 2016;122:2371-8. [Crossref] [PubMed]
10. Zhang J, Wang H, Li BG. Prognostic significance of circulating tumor cells in small--cell lung cancer patients: a meta-analysis. Asian Pac J Cancer Prev 2014;15:8429-33. [Crossref] [PubMed]
11. Kalemkerian GP, Loo BW, Akerley W, et al. NCCN guidelines Small Cell Lung Cancer. Version 3.2017. Available online: https://www.nccn.org/professionals/physician_gls/pdf/sclc.pdf
12. Peifer M, Fernández-Cuesta L, Sos ML, et al. Integrative genome analyses identify key somatic driver mutations of small cell lung cancer. Nat Genet 2012;44:1104-10. [Crossref] [PubMed]
13. Ni X, Zhuo M, Su Z, et al. Reproducible copy number variation patterns among single circulating tumor cells of lung cancer patients. Proc Natl Acad Sci U S A 2013;110:21083-8. [Crossref] [PubMed]
14. Carter L, Rothwell DG, Mesquita B, et al. Molecular analysis of circulating tumor cells identifies distinct copy-number profiles in patients with chemosensitive and chemorefractory small-cell lung cancer. Nat Med 2017;23:114-9. [Crossref] [PubMed]
15. Rudin CM, Durinck S, Stawiski EW, et al. Comprehensive genomic analysis identifies SOX2 as a frequently amplified gene in small-cell lung cancer. NAt Genet 2012;44:1111-6. [Crossref] [PubMed]
16. Tamminga M, Groen HH, Hiltermann TJ. Investigating CTCs in NSCLC-a reaction to the study of Jia-Wei Wan: a preliminary study on the relationship between circulating tumor cells count and clinical features in patients with non-small cell lung cancer. J Thorac Dis 2016;8:1032-6. [Crossref] [PubMed]
17. Chudasama DY, Freydina DV, Freidin MB, et al. Inertia based microfluidic capture and characterisation of circulating tumour cells for the diagnosis of lung cancer. Ann Transl Med 2016;4:480. [Crossref] [PubMed]
18. Swennenhuis JF, Tibbe AGJ, Stevens M, et al. Self-seeding microwell chip for the isolation and characterization of single cells. Lab Chip 2015;15:3039-46. [Crossref] [PubMed]
19. de Wit S, van Dalum G, Lenferink AT, et al. The detection of EpCAM(+) and EpCAM(-) circulating tumor cells. Sci Rep 2015;5:12270. [Crossref] [PubMed]
20. Laget S, Broncy L, Hormigos K, et al. Technical Insights into Highly Sensitive Isolation and Molecular Characterization of Fixed and Live Circulating Tumor Cells for Early Detection of Tumor Invasion. PLoS One 2017;12:e0169427 [Crossref] [PubMed]
21. Ilie M, Long E, Butori C, et al. ALK-gene rearrangement: A comparative analysis on circulating tumour cells and tumour tissue from patients with lung adenocarcinoma. Ann Oncol 2012;23:2907-13. [Crossref] [PubMed]
22. Ma YC, Wang L, Yu FL. Recent advances and prospects in the isolation by size of epithelial tumor cells (ISET) methodology. Technol Cancer Res Treat 2013;12:295-309. [PubMed]
23. Hofman VJ, Ilie MI, Bonnetaud C, et al. Cytopathologic detection of circulating tumor cells using the isolation by size of epithelial tumor cell method: Promises and pitfalls. Am J Clin Pathol 2011;135:146-56. [Crossref] [PubMed]
24. Pinzani P, Salvadori B, Simi L, et al. Isolation by size of epithelial tumor cells in peripheral blood of patients with breast cancer: correlation with real-time reverse transcriptase-polymerase chain reaction results and feasibility of molecular analysis by laser microdissection. Hum Pathol 2006;37:711-8. [Crossref] [PubMed]
25. Hofman V, Ilie M, Long-Mira E, et al. Usefulness of immunocytochemistry for the detection of the BRAF(V600E) mutation in circulating tumor cells from metastatic melanoma patients. J Invest Dermatol 2013;133:1378-81. [Crossref] [PubMed]
26. Fernandez-Cuesta L, Perdomo S, Avogbe PH, et al. Identification of Circulating Tumor DNA for the Early Detection of Small-cell Lung Cancer. EBioMedicine 2016;10:117-23. [Crossref] [PubMed]
27. Nilsson RJ, Balaj L, Hulleman E, et al. Blood platelets contain tumor-derived RNA biomarkers. Blood 2011;118:3680-3. [Crossref] [PubMed]
28. Best MG, Sol N, Kooi I, et al. RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics. Cancer Cell 2015;28:666-76. [Crossref] [PubMed]