Open Access

Morphologic and molecular study of lung cancers associated with idiopathic pulmonary fibrosis and other pulmonary fibroses

  • Alice Guyard1,
  • Claire Danel1,
  • Nathalie Théou-Anton2,
  • Marie-Pierre Debray3,
  • Laure Gibault4,
  • Pierre Mordant5,
  • Yves Castier5,
  • Bruno Crestani6, 7,
  • Gérard Zalcman8, 9,
  • Hélène Blons10 and
  • Aurélie Cazes1, 7Email authorView ORCID ID profile
Respiratory Research201718:120

DOI: 10.1186/s12931-017-0605-y

Received: 27 January 2017

Accepted: 7 June 2017

Published: 15 June 2017

Abstract

Background

Primitive lung cancers developed on lung fibroses are both diagnostic and therapeutic challenges. Their incidence may increase with new more efficient lung fibrosis treatments. Our aim was to describe a cohort of lung cancers associated with idiopathic pulmonary fibrosis (IPF) and other lung fibrotic disorders (non-IPF), and to characterize their molecular alterations using immunohistochemistry and next-generation sequencing (NGS).

Methods

Thirty-one cancer samples were collected from 2001 to 2016 in two French reference centers for pulmonary fibrosis - 18 for IPF group and 13 for non-IPF group. NGS was performed using an ampliseq panel to analyze hotspots and targeted regions in 22 cancer-associated genes. ALK, ROS1 and PD-L1 expressions were assessed by immunohistochemistry.

Results

Squamous cell carcinoma was the most frequent histologic subtype in the IPF group (44%), adenocarcinoma was the most frequent subtype in the non-IPF group (62%). Forty-one mutations in 13 genes and one EGFR amplification were identified in 25 samples. Two samples had no mutation in the selected panel. Mutations were identified in TP53 (n = 20), MET (n = 4), BRAF (n = 3), FGFR3, PIK3CA, PTEN, STK11 (n = 2), SMAD4, CTNNB1, DDR2, ERBB4, FBXW7 and KRAS (n = 1) genes. No ALK and ROS1 expressions were identified. PD-L1 was expressed in 10 cases (62%) with only one (6%) case >50%.

Conclusions

This extensive characterization of lung fibrosis-associated cancers evidenced molecular alterations which could represent either potential therapeutic targets either clues to the pathophysiology of these particular tumors. These findings support the relevance of large molecular characterization of every lung fibrosis-associated cancer.

Keywords

Idiopathic pulmonary fibrosis Fibrosis-associated lung cancer Next-generation sequencing

Background

Idiopathic pulmonary fibrosis (IPF) is a chronic parenchymal lung disease of severe prognosis, with a median survival of about 3 years from diagnosis [1]. An increased incidence of lung cancer has been described in IPF patients, with a significantly adverse impact on survival [26]. IPF and lung cancer are both strongly associated with tobacco-smoking. Incidence of lung cancer is also increased in non-idiopathic pulmonary fibrosis suggesting a role for inflammation and fibrosis in the development of lung tumors [7]. Common pathogenic pathways and epigenetic alterations have been described in both IPF and cancer but specific molecular analysis of lung fibrosis-associated tumors has not been published so far [8].

Lung cancer in IPF patients is a therapeutic challenge as both surgery and radiotherapy are limited by lung dysfunction and are at high risk of respiratory exacerbation. Moreover chemotherapy can also be deleterious [5, 9]. However, over the past decade a better knowledge of lung cancer biology led to major changes in the management of lung cancer patients. Targeted therapies based on biomarkers have shown clinical success. Genetic alterations differ according to histologic subtypes. In adenocarcinoma (ADC), the most common cancer type, molecular characterization is now an established procedure before any therapeutic decision [10]. In squamous cell carcinoma (SCC), some targets have been identified but need to be validated [11]. Molecular alterations in oncogenes may confer constitutive activation and oncogenic addiction as for EGFR, the first target identified in lung ADC. More recently mutated BRAF and MET were also demonstrated to be addictive oncogenes. Finally, gene fusions, for instance ALK and ROS1 are other molecular mechanisms leading to oncogene activation and are validated targets [12]. In parallel identification of the tumor immune-evasion mechanisms is the basis for innovative therapies, particularly targeting the PD-1/PD-L1 pathway. Although in need of standardization, PD-L1 expression as detected by immunohistochemistry may be a predictive biomarker of anti PD-1/PD-L1 drug’s efficacy [13].

The aim of this study was to describe a retrospective cohort of lung cancers developed on IPF and other pulmonary fibroses, and to search for molecular alterations that could either represent therapeutic targets or specific oncogenic pathways in these interstitial lung diseases (ILD).

Methods

Patients and tumors

Cases of lung fibrosis-associated lung cancer diagnosed between 2001 and 2016 were identified from clinical and pathological databases of Bichat-Claude Bernard and Georges Pompidou University hospitals (Paris, France), which are both “Competence Centers for rare pulmonary disorders”. Formalin-fixed and paraffin-embedded (FFPE) samples were retrieved from Pathology department archives. Two pathologists (AC, AG) reviewed all samples to confirm diagnoses of lung fibrosis and cancer. Cancers were classified according to the 2015 WHO Classification of Lung Tumors [14]. IPF and Idiopathic Interstitial Pneumonias were diagnosed according to American Thoracic Society–European Respiratory Society consensus criteria [1, 15]. The relationship between tumor and UIP lesions was assessed on 2 slides/tumor on surgical cases of the IPF group. This study was reviewed and approved by the CEERB Paris Nord ethics committee, under the number 16–007.

Next-generation sequencing

The percentage of tumor cells was assessed by two pathologists (AC, AG), in a macrodissection area if required. DNA extraction from FFPE tissues was performed using Maxwell® 16 (Promega, Fitchburg, Wisconsin). DNA was quantified by Qubit® 2.0 Fluorometer (Qubit® dsDNA BR Assay kit-Life Technologies-Thermo Fisher Scientific, Saint Aubin, France). Sequencing libraries were prepared from tumor FFPE DNA using Ion AmpliSeq™ Colon and Lung Cancer Research Panel V2 (Life Technologies-Thermo Fisher Scientific). This panel targets over 500 hotspot mutations in 22 colon and lung cancer-associated genes: AKT BRAF CTNNB1 EGFR ERBB2 ERBB4 FBXW7 FGFR1 FGFR2 FGFR3 KRAS MET NOTCH1 NRAS PIK3CA PTEN SMAD4 STK11 TP53 ALK DDR2 MAP2K1. The multiplex barcoded libraries were generated with Ion AmpliSeq Library kit from 3-μL of DNA corresponding to 10–30ng. Using NGS data, we developed an algorithm that was used to test the presence of gene amplifications in this series. Amplifications were subsequently validated by qPCR.

MET mutations in the intronic region before the exon 14 were researched in 3 samples (P15, P24, P30) by HRM PCR (LC480, Roche, Basel, Switzerland) followed by Sanger sequencing (abi3130, Thermo Fisher Scientific, Waltham, Massachusetts, USA), using two amplicons of 200 and 212 bp around splice sites (at least 10 bp upstream and downstream).

Mutations were referred to the COSMIC database [16]. Pathogenicity prediction was studied using SIFT, Mutation Taster, PolyPhen and UMD pathogenicity prediction softwares [1720].

Immunohistochemistry

Immunohistochemistry was performed on fresh 5-μm sections from FFPE blocks on Leica BOND-MAX (Leica Biosystems, Buffalo Grove, IL) automated staining system. Briefly, slides were deparaffinized and subjected to antigen retrieval in a pH = 9 buffer. Primary antibodies (ALK – clone 5A4 – Abcam, Cambridge, UK, 1:50 dilution; ROS-1 – clone D4D6 – Genemed Biotechnologies, San Francisco, CA, 1:100 dilution; PD-L1 – clone E1L3N – Cell Signaling Technology, Danvers, MA, 1:400 dilution) were incubated for 60, 60 and 20 min respectively. Revelation was performed with Leica BOND-MAX detection kits. ALK and ROS1 results were interpreted as positive or negative. PD-L1 result was expressed as the percentage of stained tumor cells.

Statistical analysis

Continuous variables are described by their mean and SD, and compared by use of Student’s t-test. Categorical variables are described by percentages and compared by Fisher’s exact test. Statistical analysis used Prism 5 (GraphPad Software, La Jolla, CA). P < 0.05 was considered statistically significant.

Results

Patients

Thirty-one tumor samples were collected from 30 patients (Table 1). Eighteen were collected from patients diagnosed with IPF and 13 from patients suffering from other lung fibrotic disorders: connective tissue disease-associated interstitial lung disease (CTD-ILD) n = 6, idiopathic non-specific interstitial pneumonia n = 2, pneumoconiosis n = 4, drug-induced lung fibrosis n = 1.
Table 1

Clinical features

Patient

Gender

Age (years)

Tobacco (P-Y)

Disease

CT-scan

Cancer type

Cancer location

Sampling site and mode

Idiopathic pulmonary fibrosis

 P1

M

86

<5

IPF

UIP

SCC

peripheral

Lung, biopsy

 P2

F

63

40

IPF

UIP

SCC

peripheral

Lung, biopsy

 P3

M

60

NP

IPF

UIP

SCC

peripheral

Lung, surg. resec.

 P4

M

55

40

IPF

UIP

SCC

peripheral

Lung, surg. resec.

 P5

M

41

30

IPF

UIP

SCC

peripheral

Lung, biopsy

 P6

M

69

45

IPF

UIP

SCC

proximal

LN, EBUS

 P7

M

75

30

IPF

UIP

SCC

peripheral

Lung, surg. resec.

 P8

M

66

yes (NS)

likely IPF

UIP

SCC

peripheral

Lung, surg. resec.

 P9

M

68

20

IPF

UIP

ADC

peripheral

Lung, biopsy

 P10

F

56

35

IPF

UIP

ADC

peripheral

Lung, biopsy

 P3

M

61

NS

IPF

UIP

ADC

peripheral

Lung, autopsy

 P11

M

62

0

IPF

UIP

ADC

peripheral

Pleural liquid

 P12

M

58

50

IPF

UIP

ADC

peripheral

Lung, surg. resec.

 P13

M

64

40

likely IPF

UIP

ADC

peripheral

Lung, surg. resec.

 P14

M

73

55

IPF

UIP

ADS

proximal

Lung, surg. resec.

 P15

M

67

10

IPF

UIP

ADS

peripheral

Lung, surg. resec.

 P16

M

57

60

likely IPF

UIP

LCNEC

peripheral

LN, biopsy

 P30

M

51

30

IPF

UIP

SmCC

peripheral

Lung, biopsy

Connective Tissue Disease-Interstitial Lung Disease

 P18

M

57

40

RA

NSIP

SCC

proximal

Lung, surg. resec.

 P20

F

55

10

RA

UIP

ADC

peripheral

Lung, surg. resec.

 P21

M

69

100

RA

UIP

ADC

peripheral

Lung, surg. resec.

 P24

M

62

40

RA

NSIP

ADS

peripheral

Lung, surg. resec.

 P23

M

66

30

antisynthetase sd

NSIP

ADC

peripheral

LN, biopsy

 P22

F

59

0

scleroderma

UIP

ADC

peripheral

Lung, surg. resec.

Non-specific interstitial pneumonia

 P25

M

69

70

NSIP

NSIP

ADC

peripheral

Lung, surg. resec.

 P26

F

54

60

NSIP

NSIP

ADC

peripheral

Lung, surg. resec.

Pneumoconiosis

 P17

M

64

50

pneumoconiosis

Em-UIP

SCC

peripheral

Lung, surg. resec.

 P27

M

59

17

asbestosis

UIP

ADC

peripheral

Lung, biopsy

 P19

M

58

yes (NS)

Iikely asbestosis

UIP

SCC

peripheral

Lung, biopsy

 P29

M

73

50

asbestosis

Em-UIP

SmCC

peripheral

Lung, biopsy

Drug-induced lung fibrosis

 P28

M

87

60

NC (amiodarone?)

ILD

ADC

peripheral

Lung, biopsy

ADC adenocarcinoma, ADS adenosquamous carcinoma, EBUS endobronchial ultrasound, Em emphysema, IPF idiopathic pulmonary fibrosis, LCNEC large cell neuro-endocrine carcinoma, LN lymph node, NS not specified, NSIP non-specific interstitial pneumonia, P-Y pack-years, RA rheumatoid arthritis, SCC squamous cell carcinoma, SmCC small cell carcinoma, surg. resec surgical resection, UIP usual interstitial pneumonia

Men predominate in both groups (89% in IPF group and 77% in non-IPF group, n = 0.62). No difference was observed in age (63 +/− 9.9 vs 64 +/− 9.1, p = 0.75) and tobacco use (never smoker: 5.5% vs 7.6%, p = 0.74).

Samples were collected from surgical resection (n = 16), lung core biopsy (n = 10), lymph node core biopsy/cytology (n = 3), autopsy (n = 1) and pleural fluid (n = 1). Age of FFPE material ranged from 0 to 13 years (mean = 3.5 +/− 3.3).

Pathologic characterization

Pathologic characterization is summarized in Table 2. In the IPF group, histologic subtypes were SCC (n = 8, 44%), ADC (n = 6, 33%), adenosquamous carcinoma (ADS) (n = 2, 11%), small cell carcinoma (SmCC) (n = 1, 6%) and large cell neuro-endocrine carcinoma (LCNEC) (n = 1, 6%). In the non-IPF group, histologic subtypes were ADC (n = 8, 62%), SCC (n = 3, 23%), ADS (n = 1, 8%) and SmCC (n = 1, 8%).
Table 2

Pathological features

Patient

Cancer type

Cancer differenciation

Diagnostic immunohistochemistry (IHC)

Therapeutic IHC

TTF1

p40/p63

others

ALK

ROS1

PDL1

Idiopathic pulmonary fibrosis

 P1

SCC

keratinizing

/

/

 

/

/

/

 P2

SCC

nonkeratinizing

TTF1-

p40+

 

/

/

/

 P3

SCC

basaloid,

/

p63+

CK7-

/

/

<1%

keratinizing

 P4

SCC

keratinizing

TTF1-

p40+

 

/

/

5%

 P5

SCC

nonkeratinizing

TTF1-

p63+

NapsinA- CK5/6+

/

/

/

 P6

SCC

keratinizing

TTF1-

p63+

 

/

/

/

 P7

SCC

keratinizing

TTF1-

p40+

 

/

/

10%

 P8

SCC

nonkeratinizing

TTF1-

p40+

 

/

/

0%

 P9

ADC

acinar

TTF1+

 

CK7+

neg

/

/

 P10

ADC

acinar

TTF1-

p63-

 

/

/

/

 P3

ADC

solid

TTF1+

p63-

 

neg

neg

<1%

 P11

ADC

NS

TTF1-

p63-

NapsinA+

/

/

/

 P12

ADC

mucinous

TTF1-

/

CK7+ CK20+

neg

/

/

 P13

ADC

acinar

TTF1+

p40-

CK7+ CD56-

neg

neg

1%

 P14

ADS

acinar

TTF1-

p40+

CK7+

neg

neg

20%

 P15

ADS

papillary

TTF1+

p40+

 

neg

neg

15%

 P16

LCNEC

/

TTF1-

/

chromoA+ CD56+

/

/

/

synapto + CK5/6-

 P30

SmCC

/

TTF1+

/

chromoA+ CD56+

/

/

/

synapto+

Connective Tissue Disease-Interstitial Lung Disease

 P18

SCC

keratinizing

TTF1-

p40+

 

/

/

40%

 P20

ADC

papillary

TTF1+

/

 

neg

neg

<1%

 P21

ADC

solid

TTF1+

p40-

 

neg

neg

70%

 P24

ADS

solid

TTF1+

p40+

 

neg

neg

10%

 P23

ADC

solid

TTF1+

p63-

NapsinA+

/

/

/

 P22

ADC

acinar

TTF1+

/

CK7+

neg

neg

0%

Non-specific interstitial pneumonia

 P25

ADC

acinar

TTF1+

p40+

 

neg

neg

<1%

 P26

ADC

papillary

TTF1+

/

 

neg

neg

1%

Pneumoconiosis

 P17

SCC

keratinizing

TTF1-

p40+

 

/

/

1%

 P27

ADC

solid

TTF1+

p40+

 

/

/

/

 P19

SCC

nonkeratinizing

TTF1-

p63+

CK5/6+

/

/

/

 P29

SmCC

/

TTF1-

/

CD56+

/

/

/

Drug-induced lung fibrosis

 P28

ADC

acinar

TTF1+

/

NapsinA+

/

/

/

ADC adenocarcinoma, ADS adenosquamous carcinoma, LCNEC large cell neuro-endocrine carcinoma, SCC squamous cell carcinoma, SmCC small cell carcinoma

Six of the 11 SCC (55%) were keratinizing and one was basaloid (Fig. 1a). In ADC, acinar (n = 6, 43%) and solid (n = 4, 29%) were the most frequent subtypes, both observed in IPF and non-IPF groups. Papillary (n = 2, 14%) subtype was observed in the non-IPF group and mucinous (n = 1, 7%) subtype in the IPF group (Fig. 1b). A high proportion of tumors were peripheral in both groups: 16/18 (89%) in IPF group and 12/13 (92%) in non-IPF group. In the IPF group, 7/9 surgically removed tumors were developed in close contact with peripheral honeycomb regions (Fig. 1c). Two out of 9 were in contact with emphysema lesions.
Fig. 1

Pathological and immunohistochemical characteristics of lung tumors. a Keratinising squamous cell carcinoma (P4, HES, x20 objective, scale bar:100μm) (b) Papillary adenocarcinoma (P26, HES, x20 objective, scale bar:100μm) (c) Peripheral squamous cell carcinoma developed in honeycomb lung (HES, x5 objective, scale bar:500μm) (d) Positive PD-L1 staining (P21, anti-PD-L1 immunohistochemistry, x20 objective, scale bar:100μm)

Immunohistochemistry

PD-L1 expression was assessed in all surgical resections and in the autopsy specimen, corresponding to 16 cases (6 SCC, 7 ADC and 3 ADS). Among them, 6 had less than 1% of stained tumor cells, 3 had 1% to <5%, 6 had 5% to <50% and one ADC had more than 50% of stained tumor cells. Overall, 10 tumors (62%) should be considered as expressing tumor cell membrane PD-L1 antigen in more than 1% of cells (Table 2 and Fig. 1d), and one (6%) with a high level of expression.

ALK and ROS1 expression was assessed in all ADC from surgical resections and autopsy specimen (n = 10). For two other patients, ALK expression was assessed during the patient management (P9 and P12). In all tested cases, ALK and ROS1 were negative.

Next-generation sequencing

In 27/31 samples (87%), DNA quality was sufficient for proper analysis. The mean coverage was 10,646 (median 5,687, range from 247.8 to 34,874).

NGS results are presented in Tables 3 and 4. One or more mutations were found in 25/27 samples (93%). Eleven samples (41%) had one mutation, eight (30%) two mutations, five (19%) three mutations, and one (4%) presented an EGFR gene amplification.
Table 3

NGS results, TP53 mutations

Gene

 

Mutation

 

COSMIC reference

Pathogenicity prediction

Patient

Allelic frequency

% tum cells

Lung disease

Cancer

TP53

Chr17:g.7579383T > G

c.304A > C

p.Thr102Pro

/

benign

P09

11.0

NS

IPF

ADC

Chr17:g.7578461C > A

c.469G > T

p.Val157Phe

COSM10670

pathogenic

P18

54.0

70

CTD-ILD

SCC

Chr17:g.7578457C > A

c.473G > T

p.Arg158Leu

COSM10714

pathogenic

P20

27.8

40

CTD-ILD

ADC

Chr17:g.7578454G > A

c.476C > T

p.Ala159Val

COSM11148

pathogenic

P15

44

NS

IPF

ADS

Chr17:g.7578406C > T

c.524G > A

p.Arg175His

COSM10648

pathogenic

P21

42.2

70

CTD-ILD

ADC

Chr17:g.7578388C > G

c.542G > C

p.Arg181Pro

COSM45046

pathogenic

P09

22.1

NS

IPF

ADC

Chr17:g.7578272G > T

c.577C > A

p.His193Asn

COSM43935

pathogenic

P03-ADC

59.3

70

IPF

ADC

Chr17:g.7578272G > A

c.577C > T

p.His193Tyr

COSM10672

pathogenic

P01

22.4

50

IPF

SCC

Chr17:g.7577574T > C

c.707A > G

p.Tyr236Cys

COSM10731

pathogenic

P30

84.0

70

IPF

SmCC

Chr17:g.7577559G > A

c.722C > T

p.Ser241Phe

COSM10812

pathogenic

P27

16.4

20

pneumoconiosis

ADC

Chr17:g.7577559G > A

c.722C > T

p.Ser241Phe

COSM10812

pathogenic

P29

84.7

>50

pneumoconiosis

SmCC

Chr17:g.7577539G > A

c.742C > T

p.Arg248Trp

COSM10656

pathogenic

P11

42.8

70

IPF

ADC

Chr17:g.7577535C > A

c.746G > T

p.Arg249Met

COSM43871

pathogenic

P08

28.9

40

IPF

SCC

Chr17:g.7577535C > A

c.746G > T

p.Arg249Met

COSM43871

pathogenic

P24

61.0

70

CTD-ILD

ADS

Chr17:g.7577120C > A

c.818G > T

p.Arg273Leu

COSM10779

pathogenic

P16

68.1

40

IPF

LCNEC

Chr17:g.7577115dup

c.823dup

p.Cys275Leufs*31

/

pathogenic

P04

16.2

25

IPF

SCC

Chr17:g.7577108C > A

c.830G > T

p.Cys277Phe

COSM10749

pathogenic

P02

42.5

40

IPF

SCC

Chr17:g.7577096_7577099del

c.839_842del

p.Arg280Thrfs*64

/

pathogenic

P05

63.6

30

IPF

SCC

Chr17:g.7577046C > A

c.892G > T

p.Glu298*

COSM10710

pathogenic

P19

65.1

40

pneumoconiosis

SCC

Chr17:g.7573976T > A

c.1051A > T

p.Lys351*

COSM1522202

pathogenic

P17

61.1

90

pneumoconiosis

SCC

ADC adenocarcinoma, ADS adenosquamous carcinoma, CTD-ILD connective tissue disease associated-interstitial lung disease, IPF idiopathic pulmonary fibrosis, LCNEC large cell neuro-endocrine carcinoma, NSIP non-specific interstitial pneumonia, SCC squamous cell carcinoma, SmCC small cell carcinoma

Table 4

NGS results, other mutations

Gene

 

Mutation

 

COSMIC reference

Pathogenicity prediction

Patient

Allelic frequency

% tum cells

Lung disease

Cancer

MET

Chr7:g.116340214G > A

c.1076G > A

p.Arg359Gln

COSM1286164

probably benign

P01

49.4

50

IPF

SCC

Chr7:g.116411867G > A

c.2942–36G > A

   

P15

 

NS

IPF

ADS

Chr7:g.116411923C > T

c.2962C > T

p.Arg988Cys

COSM1666978

unknown

P05

33.9

30

IPF

SCC

Chr7:g.116411992A > G

c.2977A > G

p.Thr1011Ala

/

unknown

P22

27.6

50

CTD-ILD

ADC

BRAF

Chr7:g.140481402C > G

c.1406G > C

p.Gly469Ala

COSM460

pathogenic

P17

71.8

90

pneumoconiosis

SCC

Chr7:g.140481402C > G

c.1406G > C

p.Gly469Ala

COSM460

pathogenic

P28

46.9

70

drug-induced LF

ADC

Chr7:g.140453134T > C

c.1801A > G

p.Lys601Glu

COSM478

pathogenic

P20

27.6

40

CTD-ILD

ADC

PIK3CA

Chr3:g.178936082G > A

c.1624G > A

p.Glu542Lys

COSM760

pathogenic

P28

64.2

70

drug-induced LF

ADC

Chr3:g.178936082G > A

c.1624G > A

p.Glu542Lys

COSM760

pathogenic

P15

48

NS

IPF

ADS

Chr3.g.178938847A > T

c.2089A > T

p.Met697Leu

/

unknown

P25

8.5

50

NSIP

ADC

FGFR3

Chr4:g.1806149G > C

c.1168G > C

p.Val390Leu

/

unknown

P25

9.6

50

NSIP

ADC

Chr4:g.1807891G > C

c.1950G > C

p.Lys650Asn

COSM3993568

pathogenic

P29

16.3

>50

pneumoconiosis

SmCC

PTEN

Chr10:g.89720729del

c.880del

p.Ser294Valfs*13

/

pathogenic

P02

20.1

40

IPF

SCC

Chr10:g.89720852C > T

c.1003C > T

p.Arg335*

COSM5151

pathogenic

P02

34.5

40

IPF

SCC

STK11

Chr19:g.1221249del

c.772del

p.Asp258Thrfs*29

/

pathogenic

P06

93.6

50

IPF

SCC

Chr19:g.1223125C > G

c.1062C > G

p.Phe354Leu

COSM21360

benign

P20

49.1

40

CTD-ILD

ADC

SMAD4

Chr18:g.48591865C > G

c.1028C > G

p.Ser343*

COSM14111

pathogenic

P05

17.7

30

IPF

SCC

CTNNB1

Chr3:g.41266113C > G

c.110C > G

p.Ser37Cys

COSM5679

pathogenic

P26

34.4

50

NSIP

ADC

DDR2

Chr1:g.162729689T > A

c.775T > A

p.Trp259Arg

/

pathogenic

P24

33.0

70

CTD-ILD

ADS

ERBB4

Chr2:g.212576809C > A

c.1090G > T

p.Gly364Trp

/

pathogenic

P25

18.2

50

NSIP

ADC

FBXW7

Chr4:g.153249370G > A

c.1408C > T

p.His470Tyr

/

probably pathogenic

P06

29.5

50

IPF

SCC

KRAS

Chr12:g.25398285C > A

c.34G > T

p.Gly12Cys

COSM516

pathogenic

P26

35.1

50

NSIP

ADC

EGFR amplification (6.5 copies)

P10

10

IPF

ADC

Forty-four molecular alterations were identified in 14 genes. Twenty TP53 mutations were detected (Table 3). Nine molecular alterations were found in four genes coding for tyrosine kinase receptors: point mutations in MET (4) (Fig. 2a), FGFR3 (2), ERBB4 (1) and DDR2 (1) and one EGFR amplification. Seven mutations were described in the PI3K pathway, involving PIK3CA (3), PTEN (2) and STK11 (2) genes. Four mutations involving the MAPK pathway were identified in BRAF (3) (Fig. 2b) and KRAS (1) (Table 4). Single TP53 mutations were observed in 11 patients. Single mutation in another oncogenic gene was found in one case (MET gene for P22). Multiple oncogenic activations were found in 12 patients.
Fig. 2

MET and BRAF mutations. a Three exonic mutations: p.Arg359Gln, p.Arg988Cys and p.Thr1011Ala and one intronic mutation: c.2942-36G > A were detected within MET gene. b Two p.Gly469Ala and one p.Lys601Glu BRAF mutations were detected. Diagrams were made with the Lollipops software (https://github.com/pbnjay/lollipops)

Mutations classified by histologic subtype are in SCC: TP53 (n = 8, 80%), MET (n = 2, 20%), BRAF, PTEN, SMAD4, STK11 and FBXW7 (n = 1, 10%); in ADC: TP53 (n = 6, 50%), BRAF and PIK3CA (n = 2, 17%), MET, FGFR3, STK11, CTNNB1, ERBB4, KRAS and EGFR amplification (n = 1, 8%). Two mutations of TP53 and one mutation of PIK3CA, MET and DDR2 were found in the 2 ADS.

Mutations analysed according to parenchymal disease subtype are, in IPF group: TP53 (n = 11, 73%), MET (n = 3, 20%), PTEN, SMAD4, FBXW7, STK11, PIK3CA and EGFR amplification (n = 1, 7%); in non-IPF group: TP53 (n = 8, 67%), BRAF (n = 3, 25%), FGFR3 and PIK3CA (n = 2, 17%), STK11, DDR2, MET, KRAS, ERBB4 and CTNNB1 (n = 1, 8%).

Discussion

The aim of this study was to describe a cohort of lung cancers developed on IPF and other pulmonary fibroses, and to characterize their molecular alterations. SCC was the most frequent histologic subtype in our IPF group, as mostly reported in previous studies encompassing a large period of time [3, 21]. This squamous histology could suggest specific oncogenic events in the IPF micro-environment where peripheral honeycomb-associated squamous metaplasia and dysplasia has been reported [22]. In contrast, ADC was the most frequent subtype in the heterogeneous non-IPF group, like in the general population. Acinar subtype was the most frequent ADC subtype in our cohort (43%), and invasive mucinous subtype was rare (7%), as reported in a 89 idiopathic interstitial pneumonia-associated ADC cases recent Japanese series (35.95% and 11.24% respectively), described by Kojima [23]. In another recent Japanese series on 44 UIP-associated ADC reported by Masai, invasive mucinous subtype was predominant (29.5% of ADC) [6].

Among the genes assessed in the NGS panel, we detected 43 mutations in 13 genes and an EGFR gene amplification in 25 samples.

We detected TP53 mutations in 8 SCC (80% of SCC) and 6 ADC (50% of ADC), with the same frequency as reported in the literature [11]. We also detected TP53 mutations in all other cancer subtypes. Allelic ratios suggest a loss of the second TP53 allele, as usually in cancers [24]. Detected mutations occurring in the DNA binding domain (from codon 125 to 300), especially the hotspot codons in CpG sites, are similar to those already described, according to the COSMIC public database [16]. More than one third are G > T transversions, in accordance with the high proportion of smokers [25]. Thus a specific carcinogenesis process differing from tobacco smoke DNA signature and linked to chronic lung inflammation could not be inferred from this molecular analysis.

Four MET mutations were detected in our cohort: p.Arg359Gln and p.Arg988Cys in SCC (20%), p.Thr1011Ala in one ADC (8%) and c.2942-36G > A in one ADS. In the literature, MET mutations are reported in 2% to 7% of lung ADC and in 1% of lung SCC [12]. Codon 359 is located within the SEMA domain, involved in binding with the MET-specific ligand HGF. Codons 988 and 1011 are located in the exon 14, and c.2942-36G > A in the intronic region before the exon 14, required for negative regulation of MET. Mutations involving exon 14 splicing site have been described in lung ADC, they mostly result in exon 14 skipping and ultimately in MET protein stabilization [12, 26]. Case reports have demonstrated responses to MET-inhibitors in ADC patients with METex14 alterations [26]. METex14 mutations were, so far, not reported in lung SCC. These three exonic mutations have been described as rare polymorphisms. However their functional impact remains unclear as discordant results are obtained with pathogenicity prediction softwares. For instance p.Arg988Cys, although described as a germline polymorphism (rs34589476), has been reported in numerous lung cancers, and its pathogenic role remains elusive, in vitro data supporting functional consequences [27, 28]. Interestingly, in our cohort, three MET mutations occurred in IPF and 1 in CTD-ILD with an UIP pattern on CT-scan. Whether these variants represent true oncogenic drivers or significant polymorphisms in the fibrotic process, this could suggest a specific pathway in IPF/UIP lung with activation of the HGF/MET axis [29]. The search for MET mutations in non-tumoral IPF lung would be mandatory to test these hypotheses. Of note, we looked for mutations in flanking introns of exon 14 in only three cases. Thus we cannot exclude the possibility of more MET mutations. Whether such alterations could be targetable would deserve specific clinical trials.

A p.Trp259Arg DDR2 mutation was observed in an ADS. In the literature, DDR2 mutations are found in 4% of lung SCC and in 1% of lung ADC, without hotspot mutations. Clinical response to dasatinib was reported in rare case-reports of patients with lung SCC [30].

No mutation of EGFR was observed in our cohort, although reported in 10–15% of lung ADC [12]. This result, in addition to the absence of ALK and ROS1 rearrangement, is consistent with the predominance of male smokers in our cohort. Three recent Japanese studies also described a significantly lower EGFR mutation frequency in ILD/IPF patients [5, 6, 23].

Mutations involving the MAP kinase pathway are frequent in ADC [12]. We described a p.Gly469Ala BRAF mutation in a SCC (10% of SCC), a p.Lys601Glu and a p.Gly469Ala BRAF mutation in 2 ADC (17% of ADK). In the literature, BRAF mutations are reported in about 4% of lung SCC and in 10% of lung ADC [11, 12]. BRAF mutations p.Lys601Glu and p.Gly469Ala have already been described in lung ADC. Non-V600E mutations are usual, representing about half of BRAF mutations [31]. Conversely, p.Gly469Ala has never been described in lung SCC. Both are activating BRAF mutations. BRAF and MEK inhibitors can target p.V600E BRAF mutations [31, 32]. Response rates for lung cancer patients with non-V600 mutations are unknown. Only one ADC was KRAS mutated (representing 8% of adenocarcinomas) whereas KRAS mutations are reported in more than 30% of lung ADC [12], especially in smokers. While the absence of EGFR mutation could be explained by the high smoking rate in our population, the low incidence of KRAS mutations could suggest the implication of other oncogenic drivers possibly related to the chronic lung injury during the fibrotic process. Interestingly the recent series described by Masai et al. included frequent invasive mucinous ADC (29,5%), associated with numerous KRAS mutations (30,2%) [6]. This could suggest carcinogenesis differences linked to ethnicity or be the reflect of our limited number of patients. However these results were not confirmed by Kojima et al. who reported a low rate of invasive mucinous subtype (11,24%) and no difference of KRAS mutation rate between non-UIP-ADC and UIP-ADC [23].

One SMAD4 mutation was found in one SCC-IPF tumors. SMAD4 is a tumor-suppressive gene that can cause cell cycle arrest and apoptosis of epithelial cells, and is inactivated by mutation in over half of pancreatic cancers [33]. It acts as a central mediator in the transforming growth factor-β (TGF-β) signalling pathway. SMAD4 mutations are uncommon in lung cancer, according to COSMIC database. However this signalling pathway, targeted by TGF-beta, could be of particular relevance in a lung fibrosis context. pSer343* predicted as pathogenic is located in the MH2 region which is implicated in the oligomerization of the protein which is essential for TGFbeta signalling [34].

A p.Ser37Cys CTNNB1 mutation was detected in an ADC (8%). The codon 37 is a known hotspot mutation, implied in the constitutive activation of the Wnt signalling pathway, and the p.Ser37Cys mutation has been reported in lung ADC [35]. Mutated beta-catenin (CTNNB1) accumulation is followed by translocation to the nucleus and action in a transcriptional complex involving other transcriptional regulators like YAP1 to modulate apoptosis, proliferation or epithelial-mesenchymal transition [36].

A p.His470Tyr FBXW7 mutation was detected in a SCC (10%). FBXW7 mutations are uncommon in lung cancer, according to COSMIC. FBXW7 is implicated in proteasome degradation of specific substrates and control tumorigenesis, acting on cell cycle, differentiation and apoptosis [37]. It is also involved in epithelial-to-mesenchymal transition by controlling mTOR pathway [38]. A p.Arg465His FBXW7 mutation was reported in a lung ADC; the patient benefited from the mTOR inhibitor temsirolimus [39].

Besides molecular targeted therapies, immunotherapy using checkpoint inhibitors is a new efficient therapy against lung cancer. PD-L1 is an immune-checkpoint protein, interacting with its ligand PD-1 expressed by T-cells, used by the tumoral cell to escape the antitumor immune response. Several drugs target the PD-1/PD-L1 interaction. An association between therapeutic response and PD-L1 expression on tumor cells has been described, although it is not a binary predictive marker and the PD-L1 assays need further standardization and validation [13]. PD-L1 expression was assessed in 16 surgical cases in the current work. All ADC but one had less than 5% of stained tumor cells, which, in addition to the pulmonary adverse effects of these molecules, may not plead for a first-line use of immunotherapy in these patients. This has to be investigated in larger series. As far as SCC are concerned PD-L1 expression seems to be less correlated to efficacy, at least in second-line of treatment [40].

Conclusion

We report here for the first time, to our best knowledge, an extensive pathological and molecular analysis of lung fibrosis-associated lung cancers. We found potentially actionable alterations in MET, FGFR3, ERBB4, DDR2, EGFR, BRAF, PI3KCA genes in various histologic subtypes. While most detected mutations are likely tobacco-associated TP53 mutations, others may suggest alternative oncogenesis mechanisms: notably we found MET, FGFR3, SMAD4 and CTNNB1 mutations, all genes that could potentially be involved in the lung fibrosis process, either participating to epithelial-mesenchymal transition or the regulation or TGFβ pathway. Conversely, the low prevalence of KRAS mutations, contrasting with the high percentage of smokers, also supports a role for endogenous carcinogenic mechanisms linked to lung fibrosis. Although limited by the size of the cohort, our series shows the feasibility of such systematic molecular characterization, for both therapeutic and pathophysiological purposes. The high mortality of fibrotic lung diseases implies that cancer remains a rare complication since possibly occurring late in the course of fibrosis. Two recently approved drugs, pirfenidone and nintedanib, have been shown to slow IPF progression [41], and are expected to extend survival. If confirmed this may lead to an increase of challenging cancer cases and encourage to perform a large molecular characterization to every lung fibrosis-associated cancer.

Abbreviations

ADC: 

Adenocarcinoma

ADS: 

Adenosquamous carcinoma

CTD-ILD: 

Connective tissue disease-associated interstitial lung disease

FFPE: 

Formalin-fixed and paraffin-embedded

IPF: 

Idiopathic pulmonary fibrosis

LCNEC: 

Large cell neuro-endocrine carcinoma

NGS: 

Next-generation sequencing

SCC: 

Squamous cell carcinoma

SmCC: 

Small cell carcinoma

Declarations

Acknowledgement

None.

Funding

Dr Guyard received a research grant from the «Société Française de Pathologie ». No other funding.

Availability of data and materials

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

AG and AC drafted the manuscript, performed histopathological examination of tumors and lung fibroses and molecular and immunohistochemical analyses. NTA and HB performed the molecular analyses. CD and LG performed the histopathological examination of tumors and lung fibroses. MPD, PM and YC participated in data collection and analyses. GZ, BC, HB and AC participated in the design and coordination of the study and helped to draft the manuscript. All authors have read and approved the final manuscript.

Competing interests

Pr. Crestani reports grants, personal fees and non-financial support from Boehringer-Ingelheim, Intermune/Roche, Medimmune/Astra Zeneca, personal fees from Sanofi, outside the submitted work. Pr. Zalcman reports personal fees and non-financial support from Roche, Pfizer, personal fees from BMS, Astra-Zeneca, non-financial support from GSK, Lilly, Boehringer-Ingelheim, outside the submitted work. Pr. Blons reports personal fees from Astra-Zeneca, Boehringer, Pfizer, outside the submitted work.

The other authors have no conflict of interest.

Consent for publication

Not applicable.

Ethics approval and consent to participate

This study was reviewed and approved by the CEERB Paris Nord ethics committee, under the number 16–007. Working retrospectively on archived FFPE tissues we were granted a waiver of consent for dead patients. Alive patients were informed and consent to theranostics work-up of tumoral tissue.

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Authors’ Affiliations

(1)
Département de Pathologie, Hôpital Bichat-Claude Bernard, Assistance Publique-Hôpitaux de Paris
(2)
Département de Génétique, Hôpital Bichat-Claude Bernard, Assistance Publique-Hôpitaux de Paris
(3)
Service de Radiologie, Hôpital Bichat-Claude Bernard, Assistance Publique-Hôpitaux de Paris
(4)
Service de Pathologie, Hôpital Européen Georges Pompidou, Assistance Publique-Hôpitaux de Paris
(5)
Service de chirurgie vasculaire et thoracique, Hôpital Bichat-Claude Bernard, Assistance Publique-Hôpitaux de Paris
(6)
Service de Pneumologie A, Hôpital Bichat-Claude Bernard, Assistance Publique-Hôpitaux de Paris
(7)
INSERM U1152, DHU FIRE, Labex Inflamex, Université Paris- Diderot
(8)
Service d’Oncologie Thoracique, CIC1425/CLIP2 Paris-Nord, Université Paris-Diderot, Hôpital Bichat-Claude Bernard, AP-HP
(9)
INSERM U830, Institut Curie
(10)
Department of Biochemistry, Pharmacogenetic and Molecular Oncology Unit, Hôpital Européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, INSERM UMR-S1147, Université Sorbonne Paris Cité

References

  1. Raghu G, Rochwerg B, Zhang Y, Garcia CAC, Azuma A, Behr J, et al. An Official ATS/ERS/JRS/ALAT Clinical Practice Guideline: Treatment of Idiopathic Pulmonary Fibrosis. An Update of the 2011 Clinical Practice Guideline. Am J Respir Crit Care Med. 2015;192:e3–e19.View ArticlePubMedGoogle Scholar
  2. Le Jeune I, Gribbin J, West J, Smith C, Cullinan P, Hubbard R. The incidence of cancer in patients with idiopathic pulmonary fibrosis and sarcoidosis in the UK. Respir Med. 2007;101:2534–40.View ArticlePubMedGoogle Scholar
  3. Ozawa Y, Suda T, Naito T, Enomoto N, Hashimoto D, Fujisawa T, et al. Cumulative incidence of and predictive factors for lung cancer in IPF. Respirology. 2009;14:723–8.View ArticlePubMedGoogle Scholar
  4. Tomassetti S, Gurioli C, Ryu JH, Decker PA, Ravaglia C, Tantalocco P, et al. The impact of lung cancer on survival of idiopathic pulmonary fibrosis. Chest. 2015;147:157–64.View ArticlePubMedGoogle Scholar
  5. Kanaji N, Tadokoro A, Kita N, Murota M, Ishii T, Takagi T, et al. Impact of idiopathic pulmonary fibrosis on advanced non-small cell lung cancer survival. J Cancer Res Clin Oncol. 2016;142:1855–65.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Masai K, Tsuta K, Motoi N, Shiraishi K, Furuta K, Suzuki S, et al. Clinicopathological, Immunohistochemical, and Genetic Features of Primary Lung Adenocarcinoma Occurring in the Setting of Usual Interstitial Pneumonia Pattern. J Thorac Oncol. 2016;11:2141–9.View ArticlePubMedGoogle Scholar
  7. Daniels CE, Jett JR. Does interstitial lung disease predispose to lung cancer? Curr Opin Pulm Med. 2005;11:431–7.View ArticlePubMedGoogle Scholar
  8. Vancheri C. Common pathways in idiopathic pulmonary fibrosis and cancer. Eur Respir Rev. 2013;22:265–72.View ArticlePubMedGoogle Scholar
  9. Kreuter M, Ehlers-Tenenbaum S, Schaaf M, Oltmanns U, Palmowski K, Hoffmann H, et al. Treatment and outcome of lung cancer in idiopathic interstitial pneumonias. Sarcoidosis Vasc Diffuse Lung Dis. 2015;31:266–74.PubMedGoogle Scholar
  10. Barlesi F, Mazieres J, Merlio J-P, Debieuvre D, Mosser J, Lena H, et al. Routine molecular profiling of patients with advanced non-small-cell lung cancer: results of a 1-year nationwide programme of the French Cooperative Thoracic Intergroup (IFCT). Lancet. 2016;387:1415–26.View ArticlePubMedGoogle Scholar
  11. Hammerman PS, Lawrence MS, Voet D, Jing R, Cibulskis K, Sivachenko A, et al. Comprehensive genomic characterization of squamous cell lung cancers. Nature. 2012;489:519–25.View ArticleGoogle Scholar
  12. Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511:543–50.View ArticleGoogle Scholar
  13. Kerr KM, Nicolson MC. Non-small cell lung cancer, PD-L1, and the pathologist. Arch Pathol Lab Med. 2016;140:249–54.View ArticlePubMedGoogle Scholar
  14. Travis WD, Brambilla E, Nicholson AG, Yatabe Y, Austin JHM, Beasley MB, et al. The 2015 world health organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J Thorac Oncol. 2015;10(9):1243–60.View ArticlePubMedGoogle Scholar
  15. Travis WD, Costabel U, Hansell DM, King TE, Lynch DA, Nicholson AG, et al. An Official American Thoracic Society/European Respiratory Society Statement: Update of the International Multidisciplinary Classification of the Idiopathic Interstitial Pneumonias. Am J Respir Crit Care Med. 2013;188:733–48.View ArticlePubMedGoogle Scholar
  16. Forbes SA, Beare D, Gunasekaran P, Leung K, Bindal N, Boutselakis H, et al. COSMIC: exploring the world’s knowledge of somatic mutations in human cancer. Nucleic Acids Res. 2015;43:D805–11.View ArticlePubMedGoogle Scholar
  17. Vaser R, Adusumalli S, Leng SN, Sikic M, Ng PC. SIFT missense predictions for genomes. Nat Protoc. 2015;11:1–9.View ArticlePubMedGoogle Scholar
  18. Adzhubei I, Jordan DM, Sunyaev SR. Predicting Functional Effect of Human Missense Mutations Using PolyPhen-2. In: Haines JL, Korf BR, Morton CC, Seidman CE, Seidman JG, Smith DR, editors. Curr. Protoc. Hum. Genet. Hoboken: John Wiley & Sons, Inc; 2013. [cited 2016 Sep 10]. p. 7.20.1-7.20.41Available from: http://doi.wiley.com/10.1002/0471142905.hg0720s76.Google Scholar
  19. Schwarz JM, Rödelsperger C, Schuelke M, Seelow D. MutationTaster evaluates disease-causing potential of sequence alterations. Nat Methods. 2010;7:575–6.View ArticlePubMedGoogle Scholar
  20. Salgado D, Desvignes J-P, Rai G, Blanchard A, Miltgen M, Pinard A, et al. UMD-Predictor: A High-Throughput Sequencing Compliant System for Pathogenicity Prediction of any Human cDNA Substitution. Hum Mutat. 2016;37:439–46.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Aubry M-C, Myers JL, Douglas WW, Tazelaar HD, Washington Stephens TL, Hartman TE, et al. Primary pulmonary carcinoma in patients with idiopathic pulmonary fibrosis. Mayo Clin Proc. 2002;77:763–70.View ArticlePubMedGoogle Scholar
  22. King TE, Pardo A, Selman M. Idiopathic pulmonary fibrosis. Lancet. 2011;378:1949–61.View ArticlePubMedGoogle Scholar
  23. Kojima Y, Okudela K, Matsumura M, Omori T, Baba T, Sekine A, et al. The pathological features of idiopathic interstitial pneumonia-associated pulmonary adenocarcinomas. Histopathology. 2017;70:568–78.View ArticlePubMedGoogle Scholar
  24. Demidenko ZN, Fojo T, Blagosklonny MV. Complementation of two mutant p53: Implications for loss of heterozygosity in cancer. FEBS Lett. 2005;579:2231–5.View ArticlePubMedGoogle Scholar
  25. Hainaut P, Pfeifer GP. Patterns of p53 G-- > T transversions in lung cancers reflect the primary mutagenic signature of DNA-damage by tobacco smoke. Carcinogenesis. 2001;22:367–74.View ArticlePubMedGoogle Scholar
  26. Frampton GM, Ali SM, Rosenzweig M, Chmielecki J, Lu X, Bauer TM, et al. Activation of MET via Diverse Exon 14 Splicing Alterations Occurs in Multiple Tumor Types and Confers Clinical Sensitivity to MET Inhibitors. Cancer Discov. 2015;5:850–9.View ArticlePubMedGoogle Scholar
  27. Tjin EPM, Groen RWJ, Vogelzang I, Derksen PWB, Klok MD, Meijer HP, et al. Functional analysis of HGF/MET signaling and aberrant HGF-activator expression in diffuse large B-cell lymphoma. Blood. 2006;107:760–8.View ArticlePubMedGoogle Scholar
  28. Ma PC, Kijima T, Maulik G, Fox EA, Sattler M, Griffin JD, et al. c-MET mutational analysis in small cell lung cancer: novel juxtamembrane domain mutations regulating cytoskeletal functions. Cancer Res. 2003;63:6272–81.PubMedGoogle Scholar
  29. Crestani B, Marchand-Adam S, Quesnel C, Plantier L, Borensztajn K, Marchal J, et al. Hepatocyte growth factor and lung fibrosis. Proc Am Thorac Soc. 2012;9:158–63.View ArticlePubMedGoogle Scholar
  30. Hammerman PS, Sos ML, Ramos AH, Xu C, Dutt A, Zhou W, et al. Mutations in the DDR2 Kinase Gene Identify a Novel Therapeutic Target in Squamous Cell Lung Cancer. Cancer Discov. 2011;1:78–89.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Nguyen-Ngoc T, Bouchaab H, Adjei AA, Peters S. BRAF Alterations as Therapeutic Targets in Non–Small-Cell Lung Cancer. J Thorac Oncol. 2015;10:1396–403.View ArticlePubMedGoogle Scholar
  32. Gautschi O, Milia J, Cabarrou B, Bluthgen M-V, Besse B, Smit EF, et al. Targeted Therapy for Patients with BRAF-Mutant Lung Cancer Results from the European EURAF Cohort. J Thorac Oncol. 2015;10:1451–7.View ArticlePubMedGoogle Scholar
  33. Laklai H, Miroshnikova YA, Pickup MW, Collisson EA, Kim GE, Barrett AS, et al. Genotype tunes pancreatic ductal adenocarcinoma tissue tension to induce matricellular fibrosis and tumor progression. Nat Med. 2016;22:497–505.View ArticlePubMedPubMed CentralGoogle Scholar
  34. Miyaki M, Kuroki T. Role of Smad4 (DPC4) inactivation in human cancer. Biochem Biophys Res Commun. 2003;306:799–804.View ArticlePubMedGoogle Scholar
  35. Shigemitsu K, Sekido Y, Usami N, Mori S, Sato M, Horio Y, et al. Genetic alteration of the beta-catenin gene (CTNNB1) in human lung cancer and malignant mesothelioma and identification of a new 3p21. 3 homozygous deletion. Oncogene. 2001;20:4249–57.View ArticlePubMedGoogle Scholar
  36. Baum B, Georgiou M. Dynamics of adherens junctions in epithelial establishment, maintenance, and remodeling. J Cell Biol. 2011;192:907–17.View ArticlePubMedPubMed CentralGoogle Scholar
  37. Cao J, Ge M-H, Ling Z-Q. Fbxw7 Tumor Suppressor: A Vital Regulator Contributes to Human Tumorigenesis. Medicine (Baltimore). 2016;95, e2496.View ArticleGoogle Scholar
  38. Díaz VM, de Herreros AG. F-box proteins: Keeping the epithelial-to-mesenchymal transition (EMT) in check. Semin Cancer Biol. 2016;36:71–9.View ArticlePubMedGoogle Scholar
  39. Villaruz LC, Socinski MA. Temsirolimus therapy in a patient with lung adenocarcinoma harboring an FBXW7 mutation. Lung Cancer Amst Neth. 2014;83:300–1.View ArticleGoogle Scholar
  40. Brahmer J, Reckamp KL, Baas P, Crinò L, Eberhardt WEE, Poddubskaya E, et al. Nivolumab versus Docetaxel in Advanced Squamous-Cell Non–Small-Cell Lung Cancer. N Engl J Med. 2015;373:123–35.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Ryerson CJ, Collard HR. Hot off the breath: A big step forward for idiopathic pulmonary fibrosis. Thorax. 2014;69:791–2.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s). 2017

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