Journal of Thoracic Oncology:
ΔNp63 (p40) and Thyroid Transcription Factor-1 Immunoreactivity on Small Biopsies or Cellblocks for Typing Non-small Cell Lung Cancer: A Novel Two-Hit, Sparing-Material Approach
Pelosi, Giuseppe MD, MIAC*,†; Fabbri, Alessandra MD*; Bianchi, Fabrizio DSc, PhD‡; Maisonneuve, Patrick Eng§; Rossi, Giulio MD‖; Barbareschi, Mattia MD¶; Graziano, Paolo MD#; Cavazza, Alberto MD**; Rekhtman, Natasha MD, PhD††; Pastorino, Ugo MD‡‡; Scanagatta, Paolo MD‡‡; Papotti, Mauro MD§§
*Department of Pathology and Laboratory Medicine and ‡Division of Thoracic Surgery, Fondazione IRCCS National Cancer Institute, Milan, Italy; †Department of Medicine, Surgery and Dentistry, University of Milan School of Medicine, Milan, Italy; ‡IFOM, Istituto FIRC di Oncologia Molecolare, Milan, Italy; §Division of Epidemiology and Biostatistics, European Institute of Oncology, Milan, Italy; ‖Section of Pathologic Anatomy, Azienda Ospedaliera-Universitaria Policlinico, Modena, Italy; ¶Division of Pathologic Anatomy, Ospedale S. Chiara, Trento, Italy; #Division of Pathologic Anatomy, Ospedale San Camillo-Forlanini, Rome, Italy; **Division of Pathologic Anatomy, Ospedale S. Maria Nuova, Reggio Emilia, Italy; ††Department of Pathology, Sloan-Kettering Cancer Center, New York, New York; ‡‡Division of Thoracic Surgery, Fondazione IRCCS National Cancer Institute, Milan, Italy and §§Division of Pathologic Anatomy, San Luigi Hospital and University of Turin, Orbassano, Italy.
The authors declare no conflicts of interest.
Address for correspondence: Giuseppe Pelosi, MD, MIAC, Dipartimento di Patologia Diagnostica e Laboratorio, Fondazione IRCCS Istituto Nazionale Tumori, Via G. Venezian, 1, I-20133 Milano, Italy; E-mail: firstname.lastname@example.org; email@example.com
Introduction: Diagnosing non-small cell lung cancer on biopsy/cellblock samples by morphology may be demanding. As sparing material for molecular testing is mandatory, a minimalist immunohistochemistry (IHC)-based diagnostic approach is warranted by means of novel, reliable, and easy-to-assess biomarkers.
Methods: Forty-six consecutive biopsy/cellblock samples and the corresponding resection specimens (as the gold standard for morphology and IHC) from 30 adenocarcinomas (AD), 10 squamous carcinomas (SQC), 5 adenosquamous carcinomas (ADSQC), and 1 sarcomatoid carcinoma (SC) were IHC-evaluated for p40 [corresponding to nontransactivating ΔNp63 isoforms] and thyroid transcription factor-1 (TTF1) by semiquantitative assessment. For p40, also immunodecoration intensity was taken into account and dichotomized as strong or low.
Results: Nonrandom and overlapping distributions of the relevant markers were found in biopsy/cellblock and surgical specimens, which closely correlated with each other and the diverse tumor categories, with no differences in area under curve-receiver-operating-characteristic curves for each marker between any two samples, including p40 and p63. Diagnostic combinations were p40−/TTF1+ or TTF1− for AD (where p40 was negative, apart from 5/30 AD showing at the best 1–2% tumor cells with low intensity); p40+/TTF1− (p40 strong and by far higher than 50%) for SQC; and p40+/TTF1+ or p40+/TTF1− (p40 strong and less than 50%) for ADSQC. The single SC case was p40−/TTF1−, suggesting glandular lineage. Practically, 41/46 (89%) tumors were correctly classified by IHC on small samples, including 30 AD, 10 SQC, 1/5 ADSQC, and no SC. Underdiagnosis of ADSQC was actually because of sampling error of biopsies/cellblocks rather than insufficient biomarker robustness, whereas underdiagnosis of SC was really because of the failure of either marker to highlight epithelial-mesenchymal transition.
Conclusions: This minimalist IHC-based model of p40 and TTF1 on biopsy/cellblock samples was effective to correctly subtype most cases of lung cancer.
An emerging issue of the so-called therapeutic pathology1 in lung cancer regards the precise subtyping of non-small cell lung carcinomas (NSCLC),2 which may yet present a difficult challenge by morphology alone when dealing with limited material and/or poorly differentiated tumors.2–6 This issue is relevant to clinics, when considering that more than two-thirds of patients are still diagnosed late with locally advanced or metastatic diseases, for whom tailored therapy may be required.7 We recently have indicated that immunohistochemistry (IHC)-driven small biopsies paralleled ultimate profiling and diagnoses on surgical specimens, paving the way to its potential application to perspective clinical trials too on lung cancer.8 A paradigm shift of the traditional morphology-related approach on small cytology and/or biopsy specimens5,9 has recently been incorporated into the new IASLC/ATS/ERS classification on lung adenocarcinoma (AD), which recommends using IHC and/or multidisciplinary setting to minimize the category NSCLC-not otherwise specified (NOS) and sparing diagnostic material for predictive molecular testing.9–11 Hence, a minimalist IHC algorithm approach based on informative, reliable, reproducible, and easy-to-assess biomarkers is warmly advisable for NSCLC to be typed for the sake of clinical usefulness and tenability of costs.
We have hypothesized that, in small biopsy or cellblock samples, a two-hit diagnostic model based on thyroid transcription factor-1 (TTF1), a very popular and sensitive detector of pulmonary AD12–16 and p40, a relatively poorly known marker of squamous cell differentiation, either nonneoplastic or tumoral, related to nontransactivating (non-TA), truncated, or ΔN isoforms of the p63 gene family of nuclear transcription factors,17–19 could be helpful to better refine NSCLC diagnoses. The p63 gene encodes diverse mRNA isoforms, which are generated by the activity of two different promoters, one of which internal to exon 3, which lead to the accumulation of TAp63 isoforms acting as TA agents favoring cell cycle arrest with apoptosis and cell differentiation induction and/or ΔNp63-p40 isoforms acting as negative dominant agents, which stimulate cell proliferation and block apoptosis with unrestrained tumor cell growth.20 In the normal lung tissue, by IHC, ΔNp63-p40 is confined to the nonterminal respiratory branch21 where it consistently decorates the basal layer of the bronchial/bronchiolar epithelium and the myoepithelial cells of the bronchial glands, whereas TAp63 may be inconsistently expressed by type II pneumocytes especially in areas of fibrosis and inflammation.22
Although TTF1 is also shared by other pulmonary tumors, including neuroendocrine tumors,23–26 and, quite rarely, nonpulmonary and nonthyroidal tumors,27 p40 expression in cancer is almost always confined to the squamous cell carcinoma (SQC) domain, independently of the organ of origin22,28–34 and the squamous cell component of adenosquamous carcinoma (ADSQC) in the lung.34,35 Our previous observation that lung AD could overexpress TA p63 but not p40 isoforms at both the IHC and molecular levels (in abstract form only)36 and that p40 was consistently negative in fine-needle aspiration cytology samples of AD37 prompted us to investigate in more detail the diagnostic implications of the duet p40/TTF1 on a consecutive series of biopsy and cellblock samples of NSCLC. We hypothesized that TTF1-negative and/or strongly p63-expressing lung AD22,38 would be a diagnostic dilemma in the event of poor differentiation or inadequate morphology, so additional markers consistently negative in AD (such as p40),36,37 through an innovative algorithm, could prove to be useful tools in challenging cases.
The study was aimed at evaluating the effectiveness of a novel, two-hit IHC model of p40 and TTF1 on limited diagnostic material from 30 AD, 10 SQC, 5 ADSQC, and 1 sarcomatoid carcinoma (SC) to forecast the eventual diagnoses on surgical specimens according to the current lung cancer classification.10,39 In particular, negativity for p40 always excluded by definition SQC and ADSQC and paved the way to the likelihood of facing with AD also in the event of TTF1 negativity. The epithelial-mesenchymal transition, which is particularly developed in SC,40,41 was missed by either marker.
MATERIALS AND METHODS
Patients and Tumors
A series of 46 consecutive preoperative NSCLC samples consisting of 24 fine needle aspiration biopsy cellblocks, 12 fiberoptic bronchoscopy or transcutaneous core biopsies of pulmonary nodules, and 10 transcutaneous core biopsies of regional lymph nodes from 30 males (range, 43–77 years) and 16 females (range, 45–70 years), with the corresponding, paired surgical specimens (31 lobectomies, 14 pneumonectomies, and 1 atypical resection), were raised from the archives of the Department of Pathology and Laboratory Medicine of the IRCCS National Cancer Institute of Milan between 2006 and 2009. The lack of a previous history of cancer elsewhere in the body before sampling was also required for entering the investigation (approved by the institutional review board). Twenty-nine of the 46 patients (63%) underwent histology-guided neoadjuvant chemotherapy (CT) before radical surgery. According to the seventh edition of the TNM staging system,42 there were 4 tumors stage IA (2 CT), 4 IB (3 CT), 5 IIA (3 CT), 8 IIB (4 CT), 21 IIIA (15 CT), 3 IIIB (2 CT), and 1 IV. All biopsies and surgical specimens had been fixed in 4% buffered formaldehyde solution for 12 to 24 hours and embedded in paraffin. No special stains were used to highlight mucous deposition within tumor cells43,44 to test the robustness of our minimalist IHC approach and also because of a lower sensitivity rate of mucin stains in comparison with IHC. All the original hematoxylin and eosin (H&E)-stained sections of surgical specimens were blindly reviewed by two experienced pathologists in lung cancer (G.P. and A.F.) without knowledge of patients’ identity or original tumor categorization according to the 2004 World Health Organization classification criteria on lung cancer,39 assuming that these revised diagnoses made up the gold standard for any comparison. No revision was planned on the original H&E-stained sections of biopsies or cellblocks, inasmuch as the main end point of the study was to verify whether and what extent an innovative diagnostic approach based on the use of two biomarkers only could faithfully parallel the corresponding IHC profiles and, hence, eventual diagnoses on surgical specimens. All tumors were categorized as much definitively as possible, avoiding diagnosing NSCLC-NOS or large cell carcinoma (LCC). In particular, ADSQC was defined by morphology (concurrence of AD and SQC components, either accounting for at least 10%),39 whereas SC was outlined by the presence of sarcomatoid (giant and spindle cell) elements accounting for at least 10%.39 Large cell neuroendocrine carcinoma was excluded by morphology and IHC of appropriate pan-endocrine markers.39 So settled, the study comprised 30 AD, 10 SQC, 5 ADSQC, and 1 SC. The relatively higher proportion of ADSQC we observed in our tumor series was likely to be related to the prevalence of locally advanced stage and poorly differentiated tumors, when considering that such tumors have been reportedly associating with a particular propensity to give rise to local and distant metastases and pursue a more aggressive clinical course compared with conventional lung carcinomas.45–47 No tumor grading was tried on preoperative biopsy/cellblock samples and the 29 patients undergoing preoperative CT, whereas the remaining 17 chemonaive patients, including 9 AD, 6 SQC, and 2 ADSQC, showed all but 2 (1 G1 and 1 G2) poorly differentiated tumors.
All tumor samples, either biopsy/cellblock or surgical, were assessed for TTF1 (clones 8G7G3/1 and SPT24), p40 and p63, whereas the 5 ADSQC, 2 TTF1-negative AD, and the case of SC were also characterized for napsin-A, surfactant, cytokeratin 7 (CK7), cytokeratins 5/6 (CK5/6), desmocollin-3 (DSC-3), and vimentin to better unravel glandular (napsin-A, CK7, and surfactant) or squamous (DSC-3 and CK5/6) cell lineage or the epithelial-mesenchymal transition (vimentin), as elsewhere detailed2,8,37,40,48,49 (Table 1). Briefly, 3- to 4-μm-thick sections were reacted for 30 minutes with the relevant antibodies and then incubated with a commercially available detection kit (EnVision FLEX+, Dako, Glostrup, Denmark) following the manufacturer’s instructions and previously refined IHC methods.8 The specificity of all reactions was checked replacing the primary antibody with a nonrelated mouse immunoglobulin at a comparable dilution or using normal serum alone. Positive and negative controls were used as appropriate.
Immunoreactivity was rendered semiquantitatively on a scale from negative to 5+, taken into account the entire tumor area on paraffin-blocked samples and cellular compartmentalization of antibodies (nuclear area for TTF1, p40 and p63; cytoplasm domain for CK5/6, CK7, napsin-A and surfactant; and membrane/cytoplasm labeling for DSC-3). Tumors were considered negative if staining was completely absent in the relevant cells; 1+ cases showed immunoreactivity in up to 10% neoplastic cells, 2+ cases in 11 to 25% neoplastic cells, 3+ cases in 26 to 50% neoplastic cells, 4+ cases in 51 to 75% neoplastic cells, and 5+ cases in 76 to 100% neoplastic cells. This choice was determined by the need of minimizing variability in the slide assessment when trying punctual percentages. For p40, also the intensity of immunolabeling was taken into account, as strong if similar to the internal control represented by bronchial/bronchiolar basal cell layer or low if less intense than seen in the normal internal control.
Qualitative data were compared by Fisher exact test “t” test, Stuart-Maxwell’s test of overall marginal homogeneity (for square tables with >2 rows/columns), and McNemar’s test of overall bias or directional change (comparing the total frequency of cases above the main diagonal of the data table with the total frequency of cases below the main diagonal).50 Unsupervised and supervised hierarchic clustering analysis was performed using Cluster 3.0 software (http://www.eisenlab.org/eisen/) and visualized by using Java TreeView (http://jtreeview.sourceforge.net). The defining features of the diverse clusters corresponded to the different IHC scores used for the relevant markers. Similarity was measured using Spearman rank correlation metric, and clustering was performed by centroid linkage. Contingency analysis and relative mosaic plots were performed by means of JMP IN software (SAS Institute, Inc., Cary, NC), calculating p values through the likelihood ratio test. Mosaic plots indicated graphically the percentage (expressed from 0 to 1) of patients belonging to the different clusters after stratifying for the different tumor subtypes (AD, SQC, ADSQC, and SC). The diagnostic performance of IHC on both biopsy/cellblock samples and surgical specimens was evaluated approaching receiver-operating characteristic (ROC) analysis, comparing curves by Z-test.8,51 For all tests, two-sided p values were taken into account, with a threshold less than0.05 as being statistically significant.
In Table 2, the comparison between original diagnoses on biopsy/cellblock samples and surgical specimens is shown. It emerged that 33 (72%) of original diagnoses had been correctly classified by morphology on biopsy/cellblock samples, whereas the remaining 13 (28%) tumors had been classified as NSCLC-NOS or misdiagnosed as either SQC or AD.
By IHC, unsupervised hierarchic analysis suggested a nonrandom and overlapping distribution of the relevant markers across the tumor series under evaluation (Figure 1A–C). Supervised hierarchic analysis showed, in either type of material, that AD were mostly positive for TTF1 and essentially negative or at the best 1+ score (up to 1–2% positive cells in 5/30 cases) for p40, with p63 exhibiting 1+ to 3+ score, whereas SQC lacked TTF1 and presented with 4+/5+ score for both p40 and p63 (Figure 1B–D). ADSQC in turn showed variable coexistence of AD- and SQC-related profiles, whereas the case of SC was negative for TTF1 and p40 and showed only focal (1+ score) p63 immunoreactivity (Figure 1B–D). Pairwise comparison of each marker between any two samples by unsupervised (Figure 2A) and supervised (Figure 2B) hierarchic clustering resulted in high correlation coefficients, which ranged from 0.92 for p63 to 0.99 for p40 (Figure 2C). The very close and distinct relationship of the clusters with the diverse tumor categories in either type of material was also confirmed by mosaic plot analysis which showed overlapping of the relevant tumor profiling (Figure 3A, B). ROC analysis showed that the values of the area under curve were higher than 0.9 for each marker and relevant diagnosis in both surgical specimens and biopsy/cellblock samples (Figure 4A, B, respectively), with no significant differences after pairing the two types of samples (Supplementary file 1, http://links.lww.com/JTO/A188).
The punctual distribution of the relevant markers in paired biopsy/cellblock samples and surgical specimens according to the semiquantitative IHC scoring system and some representative pictures taken from two cases of AD, either biopsy or surgical specimen are shown in Supplementary file 2 (http://links.lww.com/JTO/A189) and Figure 5A–H, respectively. In AD, p40 was mostly negative (Figure 5H) or detectable in a minority (5/30) of tumors as an erratic (1–2%), 1+ score occurrence of stained tumor cells (Figure 5D) at variance with p63 that was much more represented in the same cases (Figure 5G–C). Moreover, p40 immunostaining intensity was strong in SQC and squamous cell component of ADSQC in comparison with the few AD showing p40 in 1 to 2% tumor cells, where it was low respect to the internal positive control. No differences were seen between any two paired tissue types for all markers but p63 in AD, and TTF1 immunoreactivity was similar in all but two AD by using either clone (Supplementary file 2, http://links.lww.com/JTO/A189). In the normal lung tissue, p40 was confined to the basal cell layer of bronchial/bronchiolar epithelium (Figure 5D–H) and in myoepithelial cells of the bronchial glands, whereas p63 could also be seen in scattered type II pneumocytes especially in areas of nonspecific pulmonary or subpleural fibrosis.
A diagnostic algorithm was then constructed on surgical specimens by crossing p40 and TTF1 according to either positive or negative profile (Figure 6). In particular, 1+ p40-scoring tumors (five cases, all AD) were regarded as being essentially negative in the algorithm, whereas any TTF1 amount was assumed to point to glandular differentiation. Hence, tumors with p40−/TTF1+ profile were all AD, whereas the p40−/TTF1− combination clustered around two AD and the case of SC (featuring a pleomorphic carcinoma composed of AD and spindle and giant cell carcinoma). The p40+/TTF1− profile featured SQC if p40 was by far higher than 50% (75–100%), whereas the five ADSQC expressed p40+/TTF1− profile in two cases (p40 < 50%) and p40+/TTF1+ profile in three cases (any amount for either marker, with mutual exclusion in two cases and occurrence in the same tumor cells in one case). By additional markers (Table 1), the five ADSQC exhibited immunoreactivity for CK7 (all cases), napsin-A (two cases), and surfactant (two cases) in the glandular component and for DSC-3 and CK5/6 in the squamous cell component, whereas the two p40−/TTF1− AD expressed variably CK7 or CK5/6 but not vimentin, and the case of SC was strongly and diffusely positive for vimentin with variable reaction for CK7 and CK5/6.
Overall, 41/46 tumors (89%) were correctly classified by IHC on biopsy/cellblocks in comparison with surgical specimens, including all cases of AD and SQC but only one of the five ADSQC and no case of SC (Table 3). The global figure of IHC-driven diagnoses, however, could be brought to 45/46 (98%) by also adding the four remaining cases of ADSQC, which featured an exclusive SQC (three cases: TTF1−/p40+, with p40 >50%) or AD (one case: TTF1−/p40+, with p40 1–2% tumor cells) component. Only SC actually escaped diagnostic recognition with p40/TTF1 duet. The sensitivity, specificity, and diagnostic accuracy rates of IHC on the biopsy/cellblock samples are presented in Table 4.
A main issue of this article, just like an inspiring principle, was to assess the validity of an IHC approach on biopsy/cellblock samples to effectively forecast the corresponding profiling and eventual diagnoses on surgical specimens when applying a novel two-hit, minimalist algorithm based on p40 and TTF1 IHC to simultaneously spare time, economic resources, and diagnostic material. Overall, our findings are in keeping with previously refined diagnostic conclusions drawn by means of a more extended immunohistochemical panel on an independent cohort of NSCLC biopsy specimens.8 The hierarchic clustering approach in light of the current lung cancer classification,39 the area under curve-ROC curve analysis for each marker and relevant diagnoses between the two types of samples, the high correlation coefficients after pairwise comparison for each marker between any two samples, the lack of differences in the immunoreactivity classes for the relevant markers when crossing biopsy/cellblock samples and surgical specimens (Supplementary file 2, http://links.lww.com/JTO/A189), and the overlapping mosaic plots between clusters and the diverse tumor categories in either type of material were all proofs supporting the belief that biopsy/cellblock samples were as reliable as surgical specimens for this two-hit IHC approach to identify different tumor categories, with particular reference for AD, SQC, and a subset of ADSQC. Such a conclusion is worthwhile because it paves the way to novel perspectives in clinical lung cancer trials too, in which the diagnostic assessment carried out by IHC would have the same and perhaps better relevance, reliability, and weight to the patient clinical management as that obtained by morphology alone, especially when considering the general accuracy of IHC to discover diverse cell differentiation lineages in poorly differentiated lung cancer.52 Although it is commonly said that clinical trials have been essentially guided by morphology, the real contribution of IHC is hard to split after this technique has entered the daily diagnostic armamentarium of most pathologists.53 To face the new scenario of dealing with lung cancer diagnoses on limited material,5 the new AD classification by IASLC/ATS/ERS has wisely proposed a stepwise methodology to ultimately classify tumors for clinical purposes, in particular suggesting a precise terminology when using morphology or other diagnostic adjuncts10 (IHC and/or multidisciplinary setting) on small-sized material. As poorly differentiated AD often are associated with shorter survival, more advanced stage54–56 and increased KRAS mutations (an adverse pronosticator for EGFR-based therapy),57 the way to ultimately identify these tumors remains crucial for therapy. Therefore, to validate our diagnostic algorithm, we implemented the minimalist panel approach only in those cases showing challenging or ambiguous phenotypes (ADSQC with p40+/TTF1+ or p40+/TTF1−; AD and SC with p40−/TT1−), paying particular attention not to exhaust the diagnostic material risking eventual molecular study. To this purpose, we would recommend staining gently with hematoxylin all tissue fragments after fixation to recognize them more easily inside tissue bags or inclusion cassettes and place them accurately along the cut surface of the blocks before trimming and immediately cutting a H&E section and five/six additional unstained sections on polarized or any adhesive-treated slides to carry out diagnostic IHC, if any, and subsequent molecular study. Interestingly, we also successfully destined negative IHC-stained sections to FISH or sequencing analysis, if required, to maximize the concept of sparing material and obtaining clinically useful results (data not shown). As p40 was a polyclonal antibody (at variance with all the other antibodies listed in Table 1), we used other commercially available detection kits (Dako Envision Flex and Ventana BenchMark XT biomarker platform system) obtaining the same results in terms of labeling pattern, staining intensity, or number of immunoreactive tumor cells (data not shown).
Although mixing cytoplasmic and nuclear markers (e.g., TTF1/DSC-3 or p63/napsin-A) into antibody cocktails could be an adequate answer in terms of sensitivity and specificity of reaction to reach valuable diagnostic results,2,37 the validation of a minimalist IHC approach to use in challenging cases is warranted especially to preserve tissue for further molecular testing.9,10 The use of nuclear (p40 and TTF1) over cytoplasmic markers for SQC (DSC-3)37 or AD (napsin-A)48,49 resulted particularly advantageous in severely damaged and shrinkaged areas of biopsies, where cytologic details were poor and residual cytoplasmic decoration is difficult to evaluate. As morphology remains a diagnostic cornerstone for a desirable use of only one AD marker and one SQC marker in demanding cases,5,10,11 we propound p40 as a more powerful diagnosticator than p63 (see also Figure 5), which may be widely expressed in up to one-third of lung AD.22,38,58,59 At variance with TTF1, p40 is diagnostically powerful and meaningful when looking at either positive or negative profiles (Figure 6). Conversely, TTF1 is diagnostically meaningful only if positive, whereas, whenever is negative in the setting of poorly differentiated tumors, it may underline diverse tumor subtypes, including SQC, AD, ADSQC, SC, and even salivary gland-type tumors (Supplementary File 3, http://links.lww.com/JTO/A190). We successfully identified all cases of SQC and AD by crossing p40 and TTF1, whereas only 20% ADSQC and none SC were actually diagnosed because of either sampling errors or failure of these marker to highlight epithelial-mesenchymal transition,40,41,60 in turn faithfully mirrored by vimentin IHC.8 In our study, we categorized tumors as much definitively as possible, avoiding diagnosing NSCLC-NOS or LCC. As LCC probably results from poor differentiation and/or tumor sampling incompleteness,2,61 we usually have been sampling the entire tumor mass or, at least, one block per centimeter in the largest size to discover at least focal and more differentiated, conventional features of glandular or squamous cell lineage (data not shown). However, even maintaining the tumor category of LCC, the p40/TTF1 duet is likely to reliably work by highlighting the underlying SQC or AD differentiation on the basis of the diverse immunoreactivity profiles expressed by tumor cells.
We here propound some simple and practical suggestive comments for the interpretation of the diverse p40/TTF1 profiles depicted in Figure 6 (Supplementary File 4, http://links.lww.com/JTO/A191) and also to confirm previously released considerations.2,8,62
TTF1 immunoreactivity points decidedly to AD differentiation (any amount and distribution), provided that p40 is essentially negative (1–2% p40-immunoreactive cells may be observed in a minority of AD but this finding does not contradict such a diagnosis) at variance with p63 that may be deceptively detected, even consistently in up to one-third of AD58,59 (see also Figure 5). Interestingly, ALK-rearranged AD are most often p63 positive63 but they lack p40 (Pelosi et al., manuscript in preparation).
Diffuse and strong p40 expression excludes AD by definition and greatly supports SQC diagnosis if the percentage of immunoreactive cells is by far greater than 50% (usually 75–100%), provided that TTF1 is completely negative (otherwise think of the possibility of facing with ADSQC and search for appropriate morphology). The immunostaining intensity for p40 is strong in SQC and the squamous cell component of ADSQC in comparison with p40-immunoreactive AD, where it is usually low relative to the internal positive control.
ADSQC diagnosis is heralded by p40+/TTF1+ profile or p40+/TTF1− profile (with p40 < 50%). Sampling error rather than biomarker robustness is likely to hamper the final recognition of ADSQC on both surgical specimens64 and biopsies/cellblocks (as in our investigation). Coexistence of glandular and squamous traits within the same tumor cells we observed in our study was previously described in pulmonary65 or esophageal66 carcinomas to testify the possibility of “amphicrine” biphenotypic tumors. The relatively higher proportion of ADSQC39 may be related to the huge prevalence (38/46 cases, 83%) of locally advanced stage or metastatic tumors and of poorly differentiated tumors (44/46 cases, 96%), when considering that ADSQC has been reportedly associating with a particular propensity to give rise to local and distant metastases and pursue an aggressive clinical course.45–47 Furthermore, the ADSQC incidence seems actually to be rising, in close parallel with a greater awareness for composite tumors in the lung67 and the generalized increase of epidemic pulmonary AD.39,64 Further study is needed on a larger caseload of ADSQC to confirm these preliminary data.
Negativity for p40 and TTF1 does exclude by definition SQC of whichever origin and suggests AD or SC (the latter suggested even on biopsy whether vimentin is diffusely and strongly positive in all tumor cells for full-blown epithelial-mesenchymal transition at variance with poorly differentiated NSCLC8), and also sarcoma, melanoma, or mesothelioma has to be ruled out by appropriate, additional markers and clinical working up.
Negativity for p40 and TTF1 plus lack of vimentin excludes confidently SC, melanoma, sarcoma, and to some extent mesothelioma, paving the way to the possibility of facing with pulmonary AD or unsuspected metastases for which a careful clinic integration is mandatory.
In conclusion, this article first provides evidence on the diagnostic performance of a two-hit minimalist IHC approach on biopsy/cellblock samples based on the duet p40/TTF1, for which either positive or negative profiles are meaningful and diagnostically helpful. In particular, we recommend relying routinely on p40 rather than p6358,59 for subclassifying NSCLC to avoid interpreting TTF1−/p63+ AD as belonging to the category of SQC-component containing tumors.
Supported by “Lega Italiana per la Lotta contro i Tumori” (LILT) and is dedicated to the memory of Carlotta, an extraordinarily lively girl, who untimely died of cancer in the prime of life. The authors thank Dr. William D. Travis for useful suggestions.
1. Smith BR. Therapeutic pathology: time to move beyond diagnostics. Hum Pathol 2008; 39: 1725–1727.
2. Rossi G, Pelosi G, Graziano P, et al.. A reevaluation of the clinical significance of histological subtyping of non–small-cell lung carcinoma: diagnostic algorithms in the era of personalized treatments. Int J Surg Pathol 2009; 17: 206–218.
3. Kerr K. Pulmonary adenocacarcinomas: classification and reporting. Histopathology 2009; 54: 12–27.
4. Pelosi G, Sonzogni A, Viale G. The classification of lung carcinoma: time to change the morphology-based approach? Int J Surg Pathol 2010; 18: 161–172.
5. Travis WD, Rekhtman N, Riley GJ, et al.. Pathologic diagnosis of advanced lung cancer based on small biopsies and cytology: a paradigm shift. J Thorac Oncol 2010; 5: 411–414.
6. Wallace W. The challenge of classifying poorly differentiated tumours of the lung. Histopathology 2009; 54: 28–42.
7. Hirsch FR, Wynes MW, Gandara DR, et al.. The tissue is the issue: personalized medicine for non-small cell lung cancer. Clin Cancer Res 2010; 16: 4909–4911.
8. Pelosi G, Rossi G, Bianchi F, et al.. Immunohistochemistry by means of widely agreed-upon markers (cytokeratins 5/6 and 7, p63, TTF1, vimentin) on small biopsies of non-small cell lung cancer effectively parallels the corresponding profiling and eventual diagnoses on surgical specimens. J Thorac Oncol 2011; 6: 1039–1049.
9. Pelosi G. The new taxonomy of lung adenocarcinoma stemming from a multidisciplinary integrated approach: novel pathology concepts and perspectives. J Thorac Oncol 2011; 6: 241–243.
10. Travis W, Brambilla E, Noguchi M, et al.. International association for the study of lung cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma. J Thorac Oncol 2011; 6: 244–285.
11. Rekhtman N, Brandt SM, Sigel CS, et al.. Suitability of thoracic cytology for new therapeutic paradigms in non-small cell lung carcinoma: high accuracy of tumor subtyping and feasibility of EGFR and KRAS molecular testing. J Thorac Oncol 2011; 6: 451–458.
12. Pelosi G, Fraggetta F, Pasini F, et al.. Immunoreactivity for thyroid transcription factor-1 in stage I non-small cell carcinomas of the lung. Am J Surg Pathol 2001; 25: 363–372.
13. Yatabe Y, Mitsudomi T, Takahashi T. TTF-1 expression in pulmonary adenocarcinomas. Am J Surg Pathol 2002; 26: 767–773.
14. Stenhouse G, Fyfe N, King G, et al.. Thyroid transcription factor 1 in pulmonary adenocarcinoma. J Clin Pathol 2004; 57: 383–387.
15. Reis-Filho JS, Carrilho C, Valenti C, et al.. Is TTF1 a good immunohistochemical marker to distinguish primary from metastatic lung adenocarcinomas? Pathol Res Pract 2000; 196: 835–840.
16. Downey P, Cummins R, Moran M, et al.. If it’s not CK5/6 positive, TTF-1 negative it’s not a squamous cell carcinoma of lung. APMIS 2008; 116: 526–529.
17. Okuyama R, Ogawa E, Nagoshi H, et al.. p53 homologue, p51/p63, maintains the immaturity of keratinocyte stem cells by inhibiting Notch1 activity. Oncogene 2007; 26: 4478–4488.
18. Yang A, Zhu Z, Kettenbach A, et al.. Genome-wide mapping indicates that p73 and p63 co-occupy target sites and have similar DNA-binding profiles in vivo. PLoS One 2010; 5: e11572.
19. Yang A, Schweitzer R, Sun D, et al.. p63 is essential for regenerative proliferation in limb, craniofacial and epithelial development. Nature 1999; 398: 714–718.
20. Nekulova M, Holcakova J, Coates P, et al.. The role of p63 in cancer, stem cells and cancer stem cells. Cell Mol Biol Lett 2011; 16: 296–327.
21. Yatabe Y. EGFR mutations and the terminal respiratory unit. Cancer Metastasis Rev 2010; 29: 23–36.
22. Pelosi G, Pasini F, Olsen Stenholm C, et al.. p63 immunoreactivity in lung cancer: yet another player in the development of squamous cell carcinomas? J Pathol 2002; 198: 100–109.
23. Folpe AL, Gown AM, Lamps LW, et al.. Thyroid transcription factor-1: immunohistochemical evaluation in pulmonary neuroendocrine tumors. Mod Pathol 1999; 12: 5–8.
24. Sturm N, Rossi G, Lantuejoul S, et al.. Expression of thyroid transcription factor-1 in the spectrum of neuroendocrine cell lung proliferations with special interest in carcinoids. Hum Pathol 2002; 33: 175–182.
25. Sturm N, Lantuejoul S, Laverriere MH, et al.. Thyroid transcription factor 1 and cytokeratins 1, 5, 10, 14 (34betaE12) expression in basaloid and large-cell neuroendocrine carcinomas of the lung. Hum Pathol 2001; 32: 918–925.
26. La Rosa S, Chiaravalli AM, Placidi C, et al.. TTF1 expression in normal lung neuroendocrine cells and related tumors: immunohistochemical study comparing two different monoclonal antibodies. Virchows Arch 2010; 457: 497–507.
28. Hibi K, Nakayama H, Taguchi M, et al.. AIS overexpression in advanced esophageal cancer. Clin Cancer Res 2001; 7: 469–472.
29. Hibi K, Trink B, Patturajan M, et al.. AIS is an oncogene amplified in squamous cell carcinoma. Proc Natl Acad Sci U S A 2000; 97: 5462–5467.
30. Senoo M, Tsuchiya I, Matsumura Y, et al.. Transcriptional dysregulation of the p73L/p63/p51/p40/KET gene in human squamous cell carcinomas: expression of Delta Np73L, a novel dominant-negative isoform, and loss of expression of the potential tumour suppressor p51. Br J Cancer 2001; 84: 1235–1241.
31. Yamaguchi K, Wu L, Caballero OL, et al.. Frequent gain of the p40/p51/p63 gene locus in primary head and neck squamous cell carcinoma. Int J Cancer 2000; 86: 684–689.
32. Iwata T, Uramoto H, Sugio K, et al.. A lack of prognostic significance regarding DeltaNp63 immunoreactivity in lung cancer. Lung Cancer 2005; 50: 67–73.
33. Morita M, Uramoto H, Nakata S, et al.. Expression of deltaNp63 in squamous cell carcinoma of the esophagus. Anticancer Res 2005; 25: 3533–3539.
34. Uramoto H, Sugio K, Oyama T, et al.. Expression of the p53 family in lung cancer. Anticancer Res 2006; 26: 1785–1790.
35. Uramoto H, Yamada S, Hanagiri T. Immunohistochemical staining with deltaNp63 is useful for distinguishing the squamous cell component of adenosquamous cell carcinoma of the lung. Anticancer Res 2010; 30: 4717–4720.
36. Pelosi G, Sonzogni A, Papotti M, et al.. Different prevalence of transactivating (TA) p63 and non-TAp63 isoforms in pulmonary adenocarcinomas: a useful diagnostic tool. Mod Pathol 2010; 23: 396A–415A.
37. Righi L, Graziano P, Fornari A, et al.. Immunohistochemical subtyping of nonsmall cell lung cancer not otherwise specified in fine-needle aspiration cytology: a retrospective study of 103 cases with surgical correlation. Cancer 2011; 117: 3416–3423.
38. Wang BY, Gil J, Kaufman D, et al.. P63 in pulmonary epithelium, pulmonary squamous neoplasms, and other pulmonary tumors. Hum Pathol 2002; 33: 921–926.
39. Travis W, Brambilla E, Muller-Hermelink H, et al.. Tumours of the Lung, Pleura, Thymus and Heart. Lyon: IARC Press; 2004.
40. Pelosi G, Fraggetta F, Nappi O, et al.. Pleomorphic carcinomas of the lung show a selective distribution of gene products involved in cell differentiation, cell cycle control, tumor growth and tumor cell motility: a clinicopathological and immunohistochemical study of 31 cases. Am J Surg Pathol 2003; 27: 1203–1215.
41. Pelosi G, Sonzogni A, De Pas T, et al.. Review article: pulmonary sarcomatoid carcinomas: a practical overview. Int J Surg Pathol 2010; 18: 103–120.
42. Sobin L, Gospodarowicz M, Wittekind C. TNM Classification of Malignant Tumours. New York: Wiley-Blackwell; 2010.
43. Loo PS, Thomas SC, Nicolson MC, et al.. Subtyping of undifferentiated non-small cell carcinomas in bronchial biopsy specimens. J Thorac Oncol 2010; 5: 442–447.
44. Nicholson AG, Gonzalez D, Shah P, et al.. Refining the diagnosis and EGFR status of non-small cell lung carcinoma in biopsy and cytologic material, using a panel of mucin staining, TTF-1, cytokeratin 5/6, and P63, and EGFR mutation analysis. J Thorac Oncol 2010; 5: 436–441.
45. Cakir E, Demirag E, Aydin M, et al.. Clinicopathologic features and prognostic significance of lung tumours with mixed histologic patterns. Acta Chir Belg 2009; 109: 489–493.
46. Cooke DT, Nguyen DV, Yang Y, et al.. Survival comparison of adenosquamous, squamous cell, and adenocarcinoma of the lung after lobectomy. Ann Thorac Surg 2010; 90: 943–948.
47. Filosso PL, Ruffini E, Asioli S, et al.. Adenosquamous lung carcinomas: a histologic subtype with poor prognosis. Lung Cancer 2011; 74: 25–29.
48. Mukhopadhyay S, Katzenstein AL. Subclassification of Non-small cell lung carcinomas lacking morphologic differentiation on biopsy specimens: utility of an immunohistochemical panel containing TTF-1, Napsin A, p63, and CK5/6. Am J Surg Pathol 2011; 35: 15–25.
49. Terry J, Leung S, Laskin J, et al.. Optimal immunohistochemical markers for distinguishing lung adenocarcinomas from squamous cell carcinomas in small tumor samples. Am J Surg Pathol 2010; 34: 1805–1811.
50. Bishop Y, Fienberg S, Holland P. Discrete Multivariate Analysis: Theory and Practice. Cambridge, Massachusetts: MIT Press; 1975.
51. Mandrekar JN. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol 2010; 5: 1315–1316.
52. Jagirdar J. Application of immunohistochemistry to the diagnosis of primary and metastatic carcinoma to the lung. Arch Pathol Lab Med 2008; 132: 384–396.
53. Rosai J. Why microscopy will remain a cornerstone of surgical pathology. Lab Invest 2007; 87: 403–408.
54. Sica G, Yoshizawa A, Sima CS, et al.. A grading system of lung adenocarcinomas based on histologic pattern is predictive of disease recurrence in stage I tumors. Am J Surg Pathol 2010; 34: 1155–1162.
55. Yoshizawa A, Motoi N, Riely GJ, et al.. Impact of proposed IASLC/ATS/ERS classification of lung adenocarcinoma: prognostic subgroups and implications for further revision of staging based on analysis of 514 stage I cases. Mod Pathol 2011; 24: 653–664.
56. Ries L, Eisner M. Cancer of the Lung. Bethesda: NIH; 2007.
57. Munfus-McCray D, Harada S, Adams C, et al.. EGFR and KRAS mutations in metastatic lung adenocarcinomas. Hum Pathol 2011; 42: 1447–1453.
58. Rekhtman N, Ang DC, Sima CS, et al.. Immunohistochemical algorithm for differentiation of lung adenocarcinoma and squamous cell carcinoma based on large series of whole-tissue sections with validation in small specimens. Mod Pathol 2011; 24: 1348–1359.
59. Travis WD, Rekhtman N. Pathological diagnosis and classification of lung cancer in small biopsies and cytology: strategic management of tissue for molecular testing. Semin Respir Crit Care Med 2011; 32: 22–31.
60. Pelosi G, Scarpa A, Manzotti M, et al.. K-ras gene mutational analysis supports a monoclonal origin of biphasic pleomorphic carcinoma of the lung. Mod Pathol 2004; 17: 538–546.
61. Rossi G, Marchioni A, Milani M, et al.. TTF-1, cytokeratin 7, 34betaE12, and CD56/NCAM immunostaining in the subclassification of large cell carcinomas of the lung. Am J Clin Pathol 2004; 122: 884–893.
62. Rossi G, Papotti M, Barbareschi M, et al.. Morphology and a limited number of immunohistochemical markers may efficiently subtype non-small-cell lung cancer. J Clin Oncol 2009; 27: e141–e142; author reply e3–e4.
63. Yoshida A, Tsuta K, Nakamura H, et al.. Comprehensive histologic analysis of ALK-rearranged lung carcinomas. Am J Surg Pathol 2011; 35: 1226–1234.
64. Sridhar KS, Raub WA Jr, Duncan RC, et al.. The increasing recognition of adenosquamous lung carcinoma (1977–1986). Am J Clin Oncol 1992; 15: 356–362.
65. McDowell EM, Trump BF. Pulmonary small cell carcinoma showing tripartite differentiation in individual cells. Hum Pathol 1981; 12: 286–294.
66. Nishimaki T, Nakagawa S, Aizawa K, et al.. Composite tumor of the esophagus with tripartite differentiation. Dig Dis Sci 1997; 42: 1041–1046.
67. Pardo J, Martinez-Penuela AM, Sola JJ, et al.. Large cell carcinoma of the lung: an endangered species? Appl Immunohistochem Mol Morphol 2009; 17: 383–392.
NSCLC; Morphology; Biopsy; Cellblock; Surgical specimen; Immunohistochemistry; Diagnosis; TTF1; p40; p63
This article has been cited 11 time(s).
Clinical Applications of The Cancer Genome Atlas Project (TCGA) for Squamous Cell Lung Carcinoma
Oncology-New York, 27(9):
HistopathologyDifferential immunohistochemical localization of desmosomal plaque-related proteins in non-small-cell lung cancerHistopathology
Clinical & Translational OncologyLung adenocarcinoma in the era of targeted therapies: histological classification, sample prioritization, and predictive biomarkersClinical & Translational Oncology
Modern PathologyDistinct profile of driver mutations and clinical features in immunomarker-defined subsets of pulmonary large-cell carcinomaModern Pathology
Archives of Pathology & Laboratory MedicineDiagnosis of Lung Cancer in Small Biopsies and Cytology Implications of the 2011 International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society ClassificationArchives of Pathology & Laboratory Medicine
International Journal of Surgical PathologyImmunohistochemical Profiling of ALK Fusion Gene-Positive Adenocarcinomas of the LungInternational Journal of Surgical Pathology
American Journal of Respiratory and Critical Care Medicine
Wanted: Lung Cancer Pathologists
American Journal of Respiratory and Critical Care Medicine, 187(4):
International Journal of Surgical PathologyDelta Np63 (p40) Distribution Inside Lung Cancer: A Driver Biomarker Approach to Tumor CharacterizationInternational Journal of Surgical Pathology
International Journal of Surgical PathologySubtyping Non-Small Cell Lung Cancer: Relevant Issues and Operative Recommendations for the Best Pathology PracticeInternational Journal of Surgical Pathology
Acta Cytologicap40: A p63 Isoform Useful for Lung Cancer Diagnosis - A Review of the Physiological and Pathological Role of p63Acta Cytologica
Human Pathologyp40 (Delta Np63) and keratin 34 beta E12 provide greater diagnostic accuracy than p63 in the evaluation of small cell lung carcinoma in small biopsy samplesHuman Pathology
Supplemental Digital Content
© 2012International Association for the Study of Lung Cancer
Highlight selected keywords in the article text.