Material and Method: Five digital images of the tumor sections were obtained from 85 laryngeal carcinomas. Proportion of epithelial tumor component and stroma were measured by a software tool, allowing the pathologists to mark 205.6 μm2 blocks on areas as carcinomatous/stromal, by clicking at the image. Totally, 3.451 mm2 tumor areas have been marked to 16.785 small square blocks for each case.

Results: Median follow up was 48 months (range 3-194). The mean tumor-stroma proportion was 48.63+18.18. There was no difference for tumor-stroma proportion when tumor location, grade, stage and perinodal invasion were considered. Although the following results were statistically insignificant, the mean tumor-stroma proportion was the lowest (37.46±12.49) for subglottic carcinomas, and it was 52.41±37.47, 50.86+19.84 and 44.56±16.91 for supraglottic, transglottic and glottic cases. The tumor-stroma proportion was lowest in cases with perinodal invasion and the highest in cases without lymph node metastasis (44.72±20.23, 47.77±17.37, 50.05±17.34). Tumor-stroma proportion was higher in the basaloid subtype compared with the classical squamous cell carcinoma (53.76±14.70 and 48.63±18.38 respectively). The overall and disease-free survival analysis did not reveal significance for tumor-stroma proportion (p=0.08, p=0.38). Only pathological stage was an independent factor for overall survival (p=0.008).

Conclusion: This is the first series investigating tumor-stroma proportion as a prognostic marker in laryngeal carcinomas proposing a new method, but the findings do not support tumor-stroma proportion as a prognostic marker.

Among all cancers, carcinoma of the larynx accounts for 2.2% in men and 0.4% in women, with an increase at the latter group, probably due to changing habits of smoking¹⁹. Most of the laryngeal carcinomas originate from the supraglottic and glottic region. Although glottic carcinomas frequently remain localized for a long time, supraglottic and subglottic carcinomas tend to spread into the pre-epiglottic region and pyriform sinus as well as base of the tongue and subglottic SCC may spread to the thyroid gland, hypopharynx, esophagus and tracheal wall. Many unfavorable prognostic factors are defined for laryngeal carcinomas, including advanced stage, subglottic localization, high microscopic grade, high number and size of involved lymph nodes, and presence of extranodal extension, epidermal growth factor receptor expression, tumor budding and DNA aneuploidy^20-25. In this study the prognostic value of TSP is investigated in laryngeal SCC for the first time, in a series of patients treated with surgery and radiotherapy.

Age, gender, tumor location, clinical tumor stage and lymph node stage, type of surgery, pathological tumor and lymph node stage and the number of metastatic lymph nodes, perinodal invasion, tumor grade, treatment scheme with radio/chemotherapy time and localization of loco/regional recurrence and distant metastasis were determined from the medical records of the patients. Second primary tumors, time of disease-related and all-cause death, and the date of the last follow-up time were recorded.

Histopathological evaluation
Hematoxylin and eosin (H&E) stained sections of the patients with SCC were re-evaluated and 5 digital images were taken from adjacent tumor areas including deepest invasive margin, from the regions with most abundant stromal component, for each case by a 3-CCD color video camera (Olympus DP70, Olympus Optical Co. Ltd., Tokyo, Japan), connected to a light microscope (Olympus BX51, Olympus Optical Co. Ltd., Tokyo, Japan) at an original magnification of x20 and they were stored at a personal computer, only excluding large necrotic regions.

Image Analysis
TSP was measured at the images mentioned above by a novel software tool developed in C++ with a Graphical User Interface for the Windows operating system Histopathological Image Atlas Editor (HIAE), allowing the pathologists to mark square blocks of the target area in two types by left or right clicking by mouse and automatically calculating the proportion of the marked areas. The two types were tumor or stroma in this study. The area of square regions, delineated by the software program automatically, which could be marked by the pathologist, was 205.6 μm2. The final result for each case was calculated by the mean of the TSP’s of five images which were obtained by examining a 3.451 mm² area which corresponds to 16.785 square blocks in total. The selection of each case took about fifteen minutes. A screen snapshot of the HIAE is presented in Figure 1. In this figure, the main window of the HIAE displaying a histopathology slide under examination is presented. Individual square regions that were marked by the expert were merged and framed onto the image and also the coverage percentage of the markings was presented by a pie chart. In this case, the areas selected as red are the tumor and the yellow are stromal components.

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Figure 1: An image sample of selected tumor area with the software Histopathological Image Atlas Editor.

Statistical analysis
The cases were grouped by TSP as low and high according to the mean of the TSP values of all the cases. Statistical analysis was conducted by Scientific Package for Social Sciences (SPSS 11). For comparison of these groups, nonparametric tests such as chi-Square were applied. The overall and disease free survival analysis was plotted by the Kaplan Meier method. For comparison of the survival of different groups, the log rank test was applied for unvaried analysis with 95% confidence interval and Cox-regression for multivariate analysis. Localization of tumor, clinical and pathological, tumor and lymph node stage, number of metastatic lymph nodes, perinodal invasion, and differentiation were evaluated as variables.

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Table I: Demographical and prognostic distributions of all cases according to proportion of tumor-stroma

Median follow up was 48 months (range 3-194). The mean TSP was 48.63+18.18. There was no difference for TSP when sex, tumor location, tumor grade, pathological and clinical tumor and lymph node stage, and perinodal invasion were considered (p=0.36, p=0.21,p=0.24, p=0.41, p=0.40, p=0.83, respectively). Although statistically insignificant, the mean TSP was the lowest for subglottic carcinomas compared with supraglottic, transglottic and glottic cases (37.46+12.49, 52.41+37.47, 50.86+19.84 and 44.56+16.91, respectively). Also TSP was lowest in cases with perinodal invasion compared with cases with metastasis but no perinodal invasion and highest in cases without lymph node metastasis (44.72+20.23, 47.77+17.37, 50.05+17.34, respectively). The mean value of TSP was higher in basaloid subtype compared with the classical SCC cases (53.76±14.70 and 48.63±18.38, respectively).

The overall and disease free survival analysis did not reveal significance with log rank for sex, tumor location, tumor grade, clinical tumor and pathological lymph node stage, and perinodal invasion as well as TSP, but significance for clinical lymph node stage (p=0.036), pathological T stage (p=0.01), pathological stage (p=0.016) and number of metastatic lymph nodes (p=0.00) (Figure 2, Table II). Only pathological stage was an independent factor with coxregression for overall survival with 95% confidence interval (p=0.008, hazard ratio=1.003; lower: 1.001, upper: 1.005) among the latter four features with statistical significance.

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Figure 2: Graphic for overall survival.

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Table II: Overall survival analysis with Log rank and “p” value. The standard error was calculated with 95% confidence interval

The importance of tumor-stroma interaction was recognized a long time ago. Stephan Paget, a surgeon and son of Sir James Paget who is recognized as the founder of scientific medical pathology, proposed the “seed and soil” hypothesis in 1889. He concluded that “the best work in pathology of cancer is done by who are studying the nature of the seed (the cancer cell); the observations of the soil (the secondary organ) may also be useful”²⁶. During the last three decades there is increasing evidence that support the role of tumor stroma in tumor invasion, metastasis, progression and prognosis.

In 1993 Dingemans et al. presented the infiltrative phenotype of colon carcinoma cells when transplanted into granulation tissue while they formed encapsulated and well differentiated tumors at undisturbed subcutaneous tumors in an experimental model²⁷. This study presented direct evidence for the importance of tumor stroma in the prognostic phenotypical features of tumor growth like the infiltrative pattern. Many other factors about tumor stroma have also been described. The tumor microenvironment consists of extracellular matrix, immune and inflammatory cells, blood vessel cells and myofibroblasts²⁸. The myofibroblasts, fibroblastic cells adjacent to cancer cell nests expressing α-smooth muscle actin, seem to be very important contributors of the tumor stroma through the secretion of matrix metalloproteinases (MMP) and their inhibitors (TIMP), cytokines and chemokines along with the neoplastic cells²⁹. Degradation of the matrix and the MMPs are crucial for invasion and metastasis³⁰. It is suggested that platelet-derived growth factor (PDGF) and transforming growth factor-β (TGF-β) expression induce myofibroblastic cell proliferation^31,32. Myofibroblasts are derived either from the bone-marrow or the multiple resident precursors; the endothelial cells, smooth muscle cells, adipocytes and stellate cells²⁹.

Recently tumor stromal cells have been shown to participate in the Warburg effect in a reverse pattern, through the stimulation of the hydrogen peroxide secretion by the tumor cells inducing pseudohypoxia in the tumor microenviroment. The stromal cells then produce and present L-lactate and ketone as well as nucleotides, fatty acids and amino acids, such as glutamine to the tumor cells as a result of aerobic glycolysis and mitophagy^33,34. All these above mentioned data support the stroma as an important predictor of tumor behavior.

The association of hypoxia, fibrosis and poor prognosis has been recognized in various tumors for some time³⁵. The production of more growth factors by more stromal cells and the encapsulation of the tumor cells by fibrosis not allowing the penetration of the immune response were proposed to explain this association along with the mechanisms described above^32,33,37,38. Depending upon all these findings, the morphological quality and quantity of tumor stroma is evaluated in different tumors as prognostic markers. The properties of the stroma are described as a prognostic marker in rectal cancer by Ueno et al who proposed mature, intermediate and immature categories¹². They identified more tumor budding, which is also a poor prognostic factor in colorectal carcinomas as well as poor prognosis in cases with immature stroma^12,38,39.

The quantity of stroma or stromal components was also described as prognostic features. Sis et al. reported desmoplasia measured by computer assisted image analysis in van Gieson stained sections as a poor prognostic factor in colorectal carcinoma¹³. Mesker et al. proposed carcinoma stroma ratio as a prognostic marker in colorectal carcinomas⁶. They estimated the TSP in tumor sections and the scored lowest percentage was considered as decisive. In this study, 50% was accepted as the cutoff point for dichotomatous categorization, and they identified tumor percentage as an independent prognostic factor in Cox regression analysis. This was followed by the study in oesophageal adenocarcinoma by Courrech Staal et al., the same method was applied but in this study “tumor-stroma ratio” terminology was used instead of percentage and the tumor stroma ratio was identified as a highly significant prognostic factor⁹. Moorman et al¹⁰ and de Kruijf et al.⁸ presented the prognostic value of tumor-stroma ratio in triple negative breast adenocarcinomas with methods similar to Mesker et al⁶. The importance of the tumor stroma ratio is also validated by the morphometric study by West et al. in colorectal adenocarcinomas⁷.

The above mentioned findings are in favor of TSP as a prognostic factor for adenocarcinomas, but there is no information about SCC other than articles about desmoplasia. The association of desmoplastic response and unfavorable prognostic histopathological findings and recurrences were described for skin SCC^14-17. de Diego SJI (40) could not detect any relationship between desmoplasia with local recurrence in laryngeal and hypopharyngeal carcinomas, but Prim et al.⁴¹ presented the desmoplasia at metastatic lymph nodes as a prognostic marker. Zidar et al. reported well differentiated SCC morphology and desmoplasia association in laryngeal SCC but they did not present prognostic data⁴². Tumor budding, a poor prognostic finding related to the type of desmoplasia in colorectal carcinomas, is also described as a prognostic marker for laryngeal SCC^12,25. Based on the lack of information about TSP in laryngeal carcinomas and the above mentioned findings, we investigated if there was any relationship between TSP and histopathological findings and survival in laryngeal SCC.

Two methods were applied in the previous series in order to determine TSP. de Kruijf et al.^8, and Courrech Staal et al.⁹ applied the methodology described by Mesker WE et al.^6, and they used semiquantitative measurements depending upon the estimation of the pathologists by visual inspection, while West et al.⁷ performed point counting with a grid of 300 points and counted tumorstroma proportion in a 9 mm² tumor region. While the former authors had selected the deepest invasive border of the neoplastic lesions at the most stroma rich regions, West et al⁷ preferred selecting areas from the luminal surface with greatest tumor cell density. These methodological differences highlight the requirement for a standard method for these measurements. In our series, we evaluated the cases as described by Mesker et al, including the invasive border but also we developed and used software allowing precise measurement in a short time. The cut point was 50% in previous series as described originally by West et al. and we used the mean value of 48.63 which was pretty close to this value⁷.

The prognostic factors in laryngeal carcinomas include tumor location, tumor type, pathological T and N stage, grade, lymphovascular invasion, perineural invasion and perinodal invasion^20-23,41,42. In this series, some of the robust prognostic markers like tumor location, grade, tumor and lymph node stage were not identified as prognostic factors as well as TSP and only pathological stage was an independent prognostic factor for overall survival. Although there are conflicting results about SCC of the larynx in terms of desmoplasia, histopathological prognostic features and prognosis, considering the results in this series it is hard to conclude that the TSP is not a prognostic marker in laryngeal carcinomas^40-42. Although statistically insignificant, the lower TSP identified associated with lymph node metastasis and perinodal invasion as well as subglottic localization, which are poor prognostic factors in laryngeal carcinomas, suggests that further evaluation may provide significant results.

It seems TSP is an important factor that needs further evaluation in SCC as well as adenocarcinomas. Although we could not find statistical significance in this series for TSP, the quantitative method described in this series might be helpful for determining TSP in other series.

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