Soft tissue sarcomas (STS) are rare human malignant neoplasms, arising mostly from stem cells within non-skeletal connective tissues. They account for approximately 1% of all human malignancies. Matrix metalloproteinases (MMPs) are enzymes involved in degradation of the extracellular matrix and their expression by cancer cells allows the cells to penetrate basement membranes and tissue matrix, thereby invading and metastasising. The most studied malignant tumours from the perspective of MMP expression and its relationship to malignant behaviour are epithelial-derived carcinomas. MMPs role in invasion and metastasis of sarcomas has been very little investigated. This is in part because of the difficulty in accumulating sufficient tumour tissue to enable statistically relevant analysis of sufficient tumours. The purpose of this thesis was to examine the expression of key MMPs - MMP-2, MMP-7, MMP-9, and MMP-14 and their inhibitors (TIMP-1 and TIMP-2) at the invasive/subcapsular edge of human malignant and benign connective tissue tumours using immunohistochemistry, a technique that allows a very high level of reaction product localisation within tumours. In three different STS types and appropriate benign equivalents, the expression of MMPs -2, -7, -9, and -14 and their inhibitors (TIMPs -1 and -2) were measured using intensity of staining and the percentage area of staining by image analysis. The results were compared between tumour types and against histological grading that is widely used as a prognostic factor. The findings from this research indicated that metalloproteinases were commonly expressed in STS and benign equivalents. There were differences in expression of some benign versus malignant neoplasms of the same group. No uniform pattern of expression of any of MMPs was observed across the tumours, but some of the data, most notably that for expression of MMP-2 and -9 indicate, a role for MMPs in malignant behaviour and some showed (e.g. MMPs -7 and -14) change in expression with the grade of malignant tumours in the same broad category. There is some evidence of an inverse relationship between MMP and appropriate TIMP expression suggesting that a failure of inhibition, as much as increased expression, is a feature of malignancy.

BACKGROUND:Serum protein acidic and rich in cysteine (SPARC) is a matricellular secreted glycoprotein that performs several cellular functions and has been implicated in tumorigenesis in a variety of tumor types. The chemotherapeutic agent nanoparticle albumin-encapsulated (NAB)-paclitaxel has been postulated to exploit SPARC expression to target neoplastic cells. SPARC's role, and potentially the role of NAB-paclitaxel, in the highly heterogeneous class of soft-tissue sarcomas (STS) has not been investigated. Our objective was to explore the pattern of SPARC expression and its prognostic significance in STS.METHODS:27 tissue specimens representing various STS histologies were stained for SPARC expression by immunohistochemistry (IHC). Staining intensity was scored blindly. Survival was determined from patients' medical records and analyzed using Kaplan-Meier and log-rank with respect to SPARC expression level.RESULTS:Elevated SPARC expression was observed in 15/27 (56%) specimens. Overall patient survival segregated strongly based on levels of SPARC expression. Patients who expressed low-to-moderate levels of SPARC exhibited median survival of 22.1months, while the median survival of patients with moderate-to-high expression levels was 4.4months (log rank / p=0.0016).CONCLUSIONS:SPARC expression is elevated in a significant proportion of STS specimens analyzed in this study, but it does not appear to correlate with specific STS histologies. Given our limited sample size, we cannot draw definitive conclusions regarding association of SPARC with STS subtype. Overall survival segregates strongly by degree of SPARC expression, with elevated expression being adverse. If validated in a larger study, our results suggest that trials in STS with agents potentially targeting SPARC, such as NAB-paclitaxel, should be stratified by SPARC expression level.

京都大学 / 0048 / 新制・論文博士 / 博士(医学) / 乙第13158号 / 論医博第2145号 / 新制||医||1029(附属図書館) / (主査)教授 川上 浩司, 教授 戸井 雅和, 教授 松田 秀一 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM

Yes / Background: Soft tissue sarcomas are heterogeneous and a major complication in their management is that the existing classification scheme is not definitive and is still evolving. Leiomyosarcomas, a major histologic category of soft tissue sarcomas, are malignant tumours displaying smooth muscle differentiation. Although defined as a single group, they exhibit a wide range of clinical behaviour. We aimed to carry out molecular classification to identify new molecular subgroups with clinical relevance. Methods: We used gene expression profiling on 20 extra-uterine leiomyosarcomas and cross-study analyses for molecular classification of leiomyosarcomas. Clinical significance of the subgroupings was investigated. Results: We have identified two distinct molecular subgroups of leiomyosarcomas. One group was characterised by high expression of 26 genes that included many genes from the sub-classification gene cluster proposed by Nielsen et al. These sub-classification genes include genes that have importance structurally, as well as in cell signalling. Notably, we found a statistically significant association of the subgroupings with tumour grade. Further refinement led to a group of 15 genes that could recapitulate the tumour subgroupings in our data set and in a second independent sarcoma set. Remarkably, cross-study analyses suggested that these molecular subgroups could be found in four independent data sets, providing strong support for their existence. Conclusions: Our study strongly supported the existence of distinct leiomyosarcoma molecular subgroups, which have clinical association with tumour grade. Our findings will aid in advancing the classification of leiomyosarcomas and lead to more individualised and better management of the disease. / Alexander Boag Sarcoma Fund.

<p>Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.</p><p>Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions. </p><p>To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.</p><p>To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology. </p><p>Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy. </p><p>Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation. </p><p>Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone. </p><p>Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted. </p><p>In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.</p> / Dissertation

Os sarcomas de partes moles constituem um grupo diverso de neoplasias que podem surgir nos tecidos conjuntivos praticamente de qualquer região do corpo. A ressonância magnética (RM) é atualmente o exame de escolha para detecção, estadiamento regional e acompanhamento desses tumores. A segmentação das lesões a partir das imagens de RM da rotina permite extrair dados quantitativos, que tem potencial para adicionar informações a análise. O propósito do estudo é avaliar a reprodutibilidade da segmentação manual de sarcomas de partes moles em imagens de RM de pacientes com diagnóstico definitivo confirmado por meio da histopatologia. Como objetivo secundário foi realizada a comparação da segmentação manual e semiautomática a fim de validar a segmentação semiautomática como método alternativo para segmentação desses tumores. Foi estudada uma coorte retrospectiva de 15 pacientes consecutivos com diagnóstico confirmado de sarcoma de partes moles acompanhados em nosso serviço, no período de janeiro de 2006 até janeiro de 2016, com imagens de RM adquiridas previamente ao tratamento e disponíveis para análise no formato DICOM. Foi utilizado o software 3D Slicer para realizar as segmentações pelos métodos manual e semiautomático. Três radiologistas fizeram as segmentações de forma independente e às cegas para permitir avaliação interobservador. Os resultados obtidos demonstram haver alta reprodutibilidade intraobservador com coeficiente de similaridade de Dice entre as segmentações variando de 0,849 a 0,979 e as distâncias Hausdorff variando de 3,53 mm a 20,96 mm e uma boa reprodutibilidade interobservador com coeficientes de similaridade de Dice variando de 0,741 a 0,972 e distâncias Hausdorff variando de 5,83 a 60,84 mm. Foi encontrada uma concordância substancial entre as segmentações realizadas pelo método semiautomático quando comparadas com as segmentações realizadas pelo método manual com coeficientes de similaridade de Dice variando de 0,871 a 0,973 e distâncias Hausdorff variando de 5,43 mm a 31,75 mm. Em relação ao tempo de segmentação não houve diferença estatisticamente significativa do método semiautomático quando comparado ao método manual (p>0,05). Também foram calculados os volumes obtidos nas diferentes segmentações e houve concordância quase perfeita entre as duas segmentações manuais realizadas pelo radiologista 1, entre as segmentações realizadas pelo radiologista 1 e pelo radiologista 2, entre as segmentações realizadas pelo radiologista 1 e pelo radiologista 3, e entre a segmentação manual e semiautomática realizadas pelo radiologista 1, sendo obtidos coeficientes de correlação intraclasse (ICC) entre 0,9927 e 0,9990. Os resultados obtidos demonstram boa reprodutibilidade intra e interobservador da segmentação manual utilizando o software 3D Slicer validando dessa forma esse método como ferramenta confiável para servir de padrão de referência em futuros estudos quantitativos desses tumores. Foi encontrada concordância quase perfeita entre as segmentações realizadas pelo método semiautomático quando comparadas com as segmentações realizadas pelo método manual, mas nossos resultados não demonstraram diferença significativa de tempo de segmentação do método semiautomático em relação ao método manual. / Soft tissue sarcomas constitute a diverse group of neoplasms that can arise in the connective tissues from virtually any region of the body. Magnetic resonance imaging (MRI) is currently the examination of choice for detection, regional staging and followup of these tumors. The segmentation of the lesions from the routine MR images allows the extraction of quantitative data, which has the potential to add information to the analysis. The purpose of the study is to evaluate the reproducibility of manual segmentation of soft tissue sarcomas in MRI images of patients with definitive diagnosis confirmed by histopathology. As a secondary objective, a comparison of manual and semiautomatic segmentation was performed to validate semiautomatic segmentation as an alternative method for segmentation of these tumors. We studied a retrospective cohort of 15 consecutive patients with confirmed diagnosis of soft tissue sarcoma accompanied at our service from January 2006 to January 2016 with MR images acquired prior to treatment and available for analysis in the DICOM format. The software was used 3D Slicer to perform segmentation by manual and semiautomatic methods. Three radiologists did the segmentations independently and blindly to allow inter-observer evaluation. The results obtained show high intraobserver reproducibility with Dice similarity coefficient between the segmentations ranging from 0.849 to 0.979 and Hausdorff distances ranging from 3.53 mm to 20.96 mm and good interobserver reproducibility with Dice similarity coefficients ranging from 0.741 to 0.972 and Hausdorff distances varying from 5.83 to 60.84 mm. A substantial agreement was found between the segmentations performed by the semiautomatic method when compared to the segmentations performed by the manual method with Dice similarity coefficients ranging from 0.871 to 0.973 and Hausdorff distances ranging from 5.43 mm to 31.75 mm. Regarding the segmentation time, there was no statistically significant difference of the semiautomatic method when compared to the manual method (p> 0.05). The volumes obtained in the different segmentations were also calculated and there was almost perfect agreement between the two manual segmentations performed by the radiologist 1, between the segmentations performed by radiologist 1 and radiologist 2, between the segmentations performed by radiologist 1 and radiologist 3, and between The manual and semi-automatic segmentation performed by the radiologist 1, and intraclass correlation coefficients (ICC) between 0.9927 and 0.9990 were obtained. The results obtained demonstrate good intra and interobserver reproducibility of the manual segmentation using 3D Slicer software, thus validating this method as a reliable tool to serve as a reference standard in future quantitative studies of these tumors. Almost perfect agreement was found between the segmentations performed by the semiautomatic method when compared to the segmentations performed by the manual method, but our results did not show a significant difference in segmentation time of the semiautomatic method in relation to the manual method.

Despite improvements in the clinical management of soft tissue sarcomas (STS), 50% of patients will die of metastatic disease that is largely unresponsive to conventional chemotherapeutic agents. The aims of this study were to identify genes and pathways that are dysregulated in progressive and metastatic STS. In addition to this, cell lines from fresh tumours were initiated and established, thus increasing the repository of cell lines available for functional studies. Recent advances in the understanding of the molecular biology of STS have thus far not resulted in the use of molecular markers for clinical prognostication. Identifying novel genes and pathways will lead to molecular diagnostic methods to better stratify prognostic groups and could identify cellular targets for more efficacious treatments. Gene expression profiling of sarcoma cell lines of increasing metastatic potential revealed over-expression of genes involved in the epidermal growth factor (EGF) and transforming growth factor beta (TGFb) pathways. Factors involved in invasion and metastasis such as integrins and MMPs were over-expressed in the cell lines with higher metastatic potential. The developmental Notch pathway and cell cycle regulators were also dysregulated. NDRG1 was significantly over-expressed in the high grade sarcoma cell line, a novel finding in sarcomas. The expression of EGFR, NDRG1 and other genes from the above pathways was validated using quantitative RT-PCR in real time (qRT-PCR). A tissue microarray (TMA) comprising STS of varying tumour grades was constructed for high throughput assessment of target proteins. EGFR, its activated form and its signal transducers were investigated using immunohistochemistry (IHC). Activated EGFR (HR 2.228, p < 0.001) and phosphorylated Akt (HR 2.032, p = 0.003) were found to be independent predictors of overall survival and both correlated with tumour grade. Of the several STS cultures initiated and maintained, two of these cell lines were fully characterised in terms of cytogenetics, telomerase and alternate lengthening of 5 telomeres (ALT) status, KIT and TP53 mutation and the expression of certain biomarkers using both qRT-PCR and IHC. In summary, transcript profiling identified several potential biomarkers of tumour progression and metastasis in STS. Crucially, activated EGFR and pAkt were found in a cohort of STS samples to correlate with clinical outcome, identifying them as potential diagnostic and therapeutic targets in the treatment of STS. Activated EGFR can be used as a diagnostic marker for patient selection, as well as for target effect monitoring. Furthermore, the cell lines established in this project will serve as valuable tools in future preclinical studies.

Tumours contain heterogeneous cell populations. A population enriched in tumour-initiating potential has been identified in soft-tissue sarcoma (STS) by the isolation of "side population" (SP) cells. In this study, we compared the gene expression profiles of SP and non-SP cells in STS and identified Hedgehog (Hh) and Notch pathways as potential candidates for the targeting of SP cells. Upon verification of the activation of these pathways in SP cells, using primary tumor xenografts in NOD-SCID mice as our experimental model, we used the Hh blocker Triparanol and the Notch blocker DAPT to demonstrate that the suppression of these pathways effectively depleted the abundance of SP cells, reduced tumour growth, and inhibited the tumour-initiating potential of the treated sarcoma cells upon secondary transplantation. The data provide additional evidence that SP cells act as tumour initiating cells and points to Hh and Notch pathways as enticing targets for developing potential cancer therapies.

Tumours contain heterogeneous cell populations. A population enriched in tumour-initiating potential has been identified in soft-tissue sarcoma (STS) by the isolation of "side population" (SP) cells. In this study, we compared the gene expression profiles of SP and non-SP cells in STS and identified Hedgehog (Hh) and Notch pathways as potential candidates for the targeting of SP cells. Upon verification of the activation of these pathways in SP cells, using primary tumor xenografts in NOD-SCID mice as our experimental model, we used the Hh blocker Triparanol and the Notch blocker DAPT to demonstrate that the suppression of these pathways effectively depleted the abundance of SP cells, reduced tumour growth, and inhibited the tumour-initiating potential of the treated sarcoma cells upon secondary transplantation. The data provide additional evidence that SP cells act as tumour initiating cells and points to Hh and Notch pathways as enticing targets for developing potential cancer therapies.

Soft tissue sarcomas account for about 1% of all malignancies. The increase in incidence of soft tissue sarcomas during the recent decades may predominantly be attributed to AIDS-related Kaposi’s sarcoma; when this tumor is excluded, conclusive evidence for an age-adjusted increase is lacking. Beside the well investigated role of the human immunodeficiency virus 1 (HIV-1) and the human herpesvirus 8 (HHV-8) in the tumorigenesis of AIDS-related Kaposi’s sarcoma and several inherited disorders, considerable evidence support a relationship between occupational chemicals as vinyl chloride, phenoxyacetic acid herbicides, chlorphenols, dioxin, medicinal measures as Thorotrast exposure and therapeutic irradiation, and the development of soft tissue sarcoma. Hormones and chronic repair processes are further probably sarcoma-promoting factors. Considering the rarity of soft tissue sarcomas despite the vast portion that soft tissues comprise in the human body, additional knowledge on the tumorigenesis of soft tissue sarcomas might considerably contribute to the understanding of the etiologic pathways of malignant tumors in humans. / Weichteilsarkome stellen etwa 1% aller bösartigen Neubildungen. Der in den vergangenen Jahrzehnten beobachtete Inzidenzanstieg geht fast ausschließlich auf die rasante Zunahme an AIDS-assoziierten Kaposi-Sarkomen zurück. Bei Außerachtlassung dieses Tumors gibt es bisher keinen schlüssigen Beweis für eine wirkliche alterskorrigierte Häufigkeitszunahme der Weichteilsarkome. Neben der gut untersuchten Rolle des HIV-1-Virus und des humanen Herpes-Virus 8 bei der Entstehung des AIDS-assoziierten Kaposi-Sarkoms und einigen prädisponierenden genetischen Erkrankungen existieren starke Hinweise für einen Zusammenhang zwischen Industriegiften wie Vinylchlorid, Phenoxyessigsäure-Herbiziden, Chlorphenolen, Dioxinen, medizinischen Maßnahmen wie therapeutischer Bestrahlung oder dem Einsatz von Thorotrast, und der Entwicklung von Weichteilsarkomen. Hormone und chronische Reparaturprozesse sind weitere wahrscheinlich fördernde Einflüsse auf die Entstehung von Weichteilsarkomen. Die Tatsache, daß trotz des großen Anteils, den die Binde- und Stützgewebe an der Körpermasse stellen, nur selten maligne Tumoren von diesen Strukturen ausgehen, läßt hoffen, daß ein besseres Verständnis der an der Kanzerogenese von Weichteilsarkomen beteiligten Mechanismen in der Zukunft wichtige Erkenntnisse über die Entstehung menschlicher Tumoren liefern kann. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.