American Journal of Respiratory Cell and Molecular Biology

To the Editor:

Lung cancer is the most commonly diagnosed solid malignancy and the leading cause of mortality among all cancers (1). It is well established that lung cancer usually coexists with chronic obstructive pulmonary disease (COPD), as both diseases feature previous exposures to tobacco smoke. Moreover, recent data suggest a potential link between lung cancer and other respiratory diseases. For instance, Cabezas and colleagues found that ∼50% of patients with lung cancer also suffered from moderate to severe obstructive sleep apnea (OSA) (2), and Dreher and colleagues described a similarly high prevalence of OSA in patients with newly diagnosed lung cancer (3).

Tumor hypoxia has been widely associated with poor prognosis in several types of cancer (4). Thus, episodically low systemic oxygen levels caused by most respiratory diseases (e.g., COPD, interstitial lung disease, asthma, OSA, and obesity hypoventilation syndrome) could contribute to tumor progression. Indeed, lung cancer is more aggressive in patients with COPD (5), and the magnitude of intermittent hypoxia (IH) in OSA was recently linked to both cancer incidence and cancer mortality (6). Interestingly, experimental studies have described enhanced malignant properties of lung cancer in response to both sustained hypoxia (SH) and IH (79). These observations are therefore translationally relevant, as the high prevalence of OSA in the general population makes its coexistence with other respiratory diseases very probable, and the co-occurrence of these two conditions (sometimes termed overlap syndrome) can elicit a more severe nocturnal hypoxemia (10). However, the potential link between hypoxia and major subtypes of lung cancer remains largely unexplored.

In this context, we report our findings from a study investigating the effect of different patterns of hypoxia on a panel of cell lines harboring representative oncogenic mutations of the most prevalent histological subtypes of non–small cell lung cancer (adenocarcinoma and squamous cell carcinoma), including p53 and endothelial growth factor receptor (EGFR). Specifically, H522, H1437 (human adenocarcinoma; p53 mutant and EGFR wild-type), H1975 (human adenocarcinoma; p53 mutant, EGFR mutant), and H520 (human squamous cell lung cancer; p53 mutant, EGFR wild-type) cells were exposed for 48 hours to either normoxia (13% O2, which corresponds to normal arterial blood oxygen levels), SH (7% O2, mimicking a patient presenting with impaired lung function), or two types of IH (oscillating between 13% and 7% to mimic moderate OSA, and oscillating between 7% and 4%, which would correspond to the overlap syndrome). Cells were subjected to each profile by using a recently described lung-on-a-chip setup (11), to reproduce the high frequency of IH (60 cycles/h) that occurs in patients with severe OSA (12) (Figure 1). Cell proliferation and expression of epithelial cell adhesion molecule (EpCAM), which has been associated with lung cancer cell survival (13), were quantified by flow cytometry. Differences between the effects induced by the various hypoxic patterns as applied on each cancer cell type were assessed by two-way ANOVA. In a second set of experiments (n = 5), the protein localization of hypoxia-inducible factor 1α (HIF-1α) to the nucleus as an indicator of its activation was estimated by immunofluorescence as previously described (11). Briefly, after gas exposure, cells were fixed and stained with rabbit anti–HIF-1α (Novus Biologicals) antibody and DAPI (Sigma-Aldrich). Five epifluorescence images were acquired with an inverted microscope using a 20× Plan Fluor multi-immersion objective (0.75 NA) for each experiment. The total cellular fluorescence of HIF-1α was measured by adjusting Huang’s thresholding to subtract the background and delimit cells. The nuclear intensity of HIF-1α was estimated from the nuclear outlines identified by the DAPI channel. Cytoplasmic HIF-1α was calculated by subtracting the nuclear intensity from the whole-cell intensity. Finally, the translocation of HIF-1α to the nuclei was estimated as the nuclear/cytoplasmic fluorescence intensity ratio.

Figure 1 shows that different hypoxic profiles differentially stimulated cell proliferation in most cancer cell lines and EpCAM expression in selected cell lines. In terms of tumor cell proliferation, the most severe hypoxic IH pattern, corresponding to the overlap syndrome, only enhanced the proliferation of squamous cell carcinoma (H520) (∼66%, P < 0.001), whereas the IH profile mimicking OSA alone enhanced the tumor cell growth rate in H520 cells (∼72%, P < 0.001) and H1437 adenocarcinoma cells (∼40%, P = 0.043) compared with that observed in normoxic control conditions. Application of SH promoted an increase in tumor cell proliferation (∼56%, P = 0.005) in only one of the cancer cell types (H1437, adenocarcinoma). However, none of the hypoxic profiles elicited measurable changes in the proliferative rates of the two other adenocarcinoma cell lines (i.e., H522 and H1975). Similarly, EpCAM showed heterogeneous responses among the different human lung cancer cell types. As shown in Figure 1, H522 cells increased EpCAM expression under IH stimuli (∼47%, P < 0.001, and ∼74%, P < 0.001 for IH mimicking OSA and overlap syndrome, respectively). The H520 squamous cell carcinoma cell line also exhibited increased EpCAM expression in response to SH (∼20%, P = 0.014) and IH mimicking the overlap syndrome (∼20%, P = 0.021) when compared with normoxia. However, the two other adenocarcinoma cell lines used, H1437 and H1975, failed to display any detectable changes in EpCAM. Thus, these results suggest that EpCAM expression in response to hypoxic stimuli is largely uncorrelated with both the p53/EGFR status and the histologic subtype. The only significant changes in HIF-1α activation were observed in H1437 and H1975 lung cancer cells: ∼20% (P = 0.022) and 2.6-fold (P = 0.047) increases when cells were exposed to IH mimicking the overlap syndrome compared with normoxia, respectively (Table 1).

Table 1. Nuclear/Cytoplasmic Ratio of Hypoxia-Inducible Factor 1α Fluorescence for Each Cell Line and Hypoxic Condition Compared with 13% Normoxia

 H522H1437H1975H520
Mean ± SEP ValueMean ± SEP ValueMean ± SEP ValueMean ± SEP Value
13% O20.70 ± 0.11 1.13 ± 0.03 0.91 ± 0.03 2.84 ± 0.28 
13–7% O22.63 ± 0.860.0981.38 ± 0.100.0591.27 ± 0.300.3193.18 ± 0.370.266
7% O20.97 ± 0.160.2611.35 ± 0.160.2081.72 ± 0.350.0782.70 ± 0.150.629
7–4% O20.92 ± 0.060.0901.36 ± 0.090.0222.39 ± 0.550.0472.78 ± 0.260.883

P values, paired t test; n = 5.

Our in vitro experiments in human lung cancer cells provide new evidence in support of the clinical data that link lung cancer malignancy with other respiratory diseases (5, 6). Most importantly, our data also suggest that the response of lung cancer cells may depend, at least in part, on the presentation of the hypoxic stimulus (8). Moreover, these results are in accord with previous findings that SH and IH exposures promoted different growth rates in a murine lung Lewis carcinoma cell line (LLC1) (7). Here, we found that the behavior of cancer cells depended on the magnitude of hypoxia during IH oscillations (13–7% O2 vs. 7–4% O2). It is expected that different frequencies with similar oscillations could modulate the response of lung cancer cells, as was previously reported for melanoma (14). Furthermore, other potential factors, such as host immunity and aging, could also modulate the malignant properties of lung cancer cells in a specific hypoxic environment (7, 15).

Thus, it is important to devote further efforts to identify the target lung cancer cell types that are susceptible to hypoxia-mediated regulation, and particularly those that are affected by profiles such as those represented by IH. In this context, information on these specific issues and an improved understanding of the underlying mechanisms could potentially guide future epidemiological/clinical studies aimed at detecting incipient relationships between lung cancer and other respiratory diseases. Mechanistically, these potential relationships are likely to be complex and involve specific cancer cell mutations that are ultimately responsible for the increased cancer progression observed in response to hypoxia. Studying the effects of different hypoxic profiles in lung cancer could help investigators elucidate the roles played by COPD, OSA, and other respiratory diseases in the initiation and progression of lung cancer, thus providing the opportunity to design novel personalized therapies.

The authors thank Miguel Ángel Rodríguez for technical support, and Luca Roz and Giulia Bertolini for helpful discussions.

1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018;68:394424.
2. Cabezas E, Perez-Warnisher MT, Troncoso MF, Gomez T, Melchor R, Pinillos EJ, et al. Sleep disordered breathing is highly prevalent in patients with lung cancer: results of the sleep apnea in lung cancer study. Respiration 2019;97:119124.
3. Dreher M, Krüger S, Schulze-Olden S, Keszei A, Storre JH, Woehrle H, et al. Sleep-disordered breathing in patients with newly diagnosed lung cancer. BMC Pulm Med 2018;18:72.
4. Muz B, de la Puente P, Azab F, Azab AK. The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy. Hypoxia (Auckl) 2015;3:8392.
5. Young RP, Hopkins RJ. Estimating overdiagnosis of lung cancer. Ann Intern Med 2013;158:635.
6. Campos-Rodriguez F, Martinez-Garcia MA, Martinez M, Duran-Cantolla J, Peña MdeL, Masdeu MJ, et al.; Spanish Sleep Network. Association between obstructive sleep apnea and cancer incidence in a large multicenter Spanish cohort. Am J Respir Crit Care Med 2013;187:99105.
7. Almendros I, Wang Y, Becker L, Lennon FE, Zheng J, Coats BR, et al. Intermittent hypoxia-induced changes in tumor-associated macrophages and tumor malignancy in a mouse model of sleep apnea. Am J Respir Crit Care Med 2014;189:593601.
8. Almendros I, Wang Y, Gozal D. The polymorphic and contradictory aspects of intermittent hypoxia. Am J Physiol Lung Cell Mol Physiol 2014;307:L129L140.
9. Hunyor I, Cook KM. Models of intermittent hypoxia and obstructive sleep apnea: molecular pathways and their contribution to cancer. Am J Physiol Regul Integr Comp Physiol 2018;315:R669R687.
10. Owens RL, Malhotra A. Sleep-disordered breathing and COPD: the overlap syndrome. Respir Care 2010;55:13331344, discussion 1344–1346.
11. Campillo N, Jorba I, Schaedel L, Casals B, Gozal D, Farré R, et al. A novel chip for cyclic stretch and intermittent hypoxia cell exposures mimicking obstructive sleep apnea. Front Physiol 2016;7:319.
12. Farré R, Almendros I, Montserrat JM, Gozal D, Navajas D. Gas partial pressure in cultured cells: patho-physiological importance and methodological approaches. Front Physiol 2018;9:1803.
13. Hase T, Sato M, Yoshida K, Girard L, Takeyama Y, Horio M, et al. Pivotal role of epithelial cell adhesion molecule in the survival of lung cancer cells. Cancer Sci 2011;102:14931500.
14. Yoon DW, So D, Min S, Kim J, Lee M, Khalmuratova R, et al. Accelerated tumor growth under intermittent hypoxia is associated with hypoxia-inducible factor-1-dependent adaptive responses to hypoxia. Oncotarget 2017;8:6159261603.
15. Torres M, Campillo N, Nonaka PN, Montserrat JM, Gozal D, Martínez-García MA, et al. Aging reduces intermittent hypoxia-induced lung carcinoma growth in a mouse model of sleep apnea. Am J Respir Crit Care Med 2018;198:12341236.
*Corresponding author (e-mail: ).

Supported in part by the Spanish Society of Pneumology and Thoracic Surgery (595/2017), the Spanish Ministry of Economy and Competitiveness (SAF2017-85574-R, DPI2017-83721-P, and SAF2016-79527-R), Fundació Privada Cellex, and the National Institutes of Health (1R01HL130984).

Author disclosures are available with the text of this letter at www.atsjournals.org.

Related

No related items
Comments Post a Comment




New User Registration

Not Yet Registered?
Benefits of Registration Include:
 •  A Unique User Profile that will allow you to manage your current subscriptions (including online access)
 •  The ability to create favorites lists down to the article level
 •  The ability to customize email alerts to receive specific notifications about the topics you care most about and special offers
American Journal of Respiratory Cell and Molecular Biology
61
4

Click to see any corrections or updates and to confirm this is the authentic version of record