The sarcoma community has made much progress in elucidating the origins of MFH in the recent past if one considers that MHF was at best depicted by a state of the art review on sarcomas by Mackall et al [61
] in 2002 with a question mark following it as arising out of a “stromal lineage”. While, we similarly believe that sarcomas are best thought of as tumors that arise from distinct stages of various differentiation lineages, we believe that recent data best supports the concept that MFH and undifferentiated sarcomas arise directly from the uncommitted MSC prior to the onset of differentiation. However, in our opinion to classify undifferentiated sarcomas as truly undifferentiated, as opposed to differentiated sarcomas with signs of commitment to a specific connective tissue lineage to evolve will require a break with the past methodologies of tumor categorization.
The classification of tumors lies within the domain of the pathologist. Pathology relies first and foremost on tumor cellular and architectural morphology. Immunohistochemistry and cytogenetics remain an adjunct to more narrowly define the diagnosis. However, to classify something that by definition has no obvious signs of differentiation (or at least not enough of them to be identified) will require to move away from morphology and immunohistochemical markers of the terminal phenotype, and to the identification of early markers of lineage differentiation. These would be markers that are expressed before the terminal phenotype could only be elucidated from understanding the molecular development of the corresponding lineage. However, even this is problematic for even if one can demonstrate that an undifferentiated tumor does not express any detectable levels of early markers for smooth muscle, fat, fibrocyte and a plethora of other lineages – how does one prove that it has no markers of all lineages?
Gene expression analyses has been proposed and demonstrated to be useful in classifying sarcomas (and other tumor types as discussed above). Advantage of this technique is that it does not require one to know any specific sets of genes or markers. A critical disadvantage is that it requires some arbitrary baseline. Consider the following problem. If one performs gene expression profiling on 10 MFHs, 10 dedifferentiated liposarcomas, 10 high grade leiomyosarcomas, etc; what one will observe is that not all of these tumor samples will associate as one would have predicted. In fact it has been our personal experience that the concordance rate between pathology classifications as performed by sarcoma-specializing pathologists both at Memorial Sloan Kettering and at Columbia is only about 80%. Furthermore, re-examination of tumor samples classifying outside of their initial classification by the pathologists have not been able shed any light on why these samples would misclassify via gene expression. Who is wrong? The pathologist or the gene expression analysis (the former would be wrong for subjective reasons while the latter of course would be wrong for technical reasons). MicroRNA based classification systems have recently started to gain stream and there have been some suggestions that they may be even better at classifying sarcomas than gene expression profiling [62
In our opinion, the current histopathologic classification process is centered predominantly on morphology. Molecular methodologies (e.g., chromosomal breakpoint analysis for specific lymphomas and sarcomas) are seen as secondary determinants to assist with the primary modality of morphological classification. And while the current limited use of molecular methodology in pathology is indeed highly complimentary to morphologic classification, we are currently not taking enough advantage of the power of molecular methodology in its ability to truly synergize and not just compliment the morphologic classification. In order for the field to evolve we must be able to see beyond just morphology and to stop using morphology as the sole standard to which all else must concord. We have tried to do this by linking gene expression analysis of MFH and the various types of liposarcomas to an in vitro adipogeneic differentiation time course. Although we set a non-subjective differentiation time line as our standard, to assert our hypothesis we nevertheless relied on groups of sarcomas that were designated as such, for the most part, solely by morphological criteria. In our opinion, future classification of sarcomas should rely on a system that gives equal weight to both morphological based determination and molecular methodology (i.e. gene expression/microRNA/epigenetic modification). Building on the potential synergism between morphologic classification and molecular methodology will we be able to truly differentiate the undifferentiated.
The other way in which we must break from the past is that we must be able to see through the heterogeneity of undifferentiated sarcomas, and to non-arbitrarily quantitate number of undifferentiated tumor cells versus differentiated tumor cells per tumor section. Our laboratory has previously reported on the use of ‘systems pathology’ focusing on computerized morphometric analysis to better define prostate cancer [63
]. Although the mathematical algorithms that define morphometric analysis are extremely complicated, they in essence employ an image segmentation process in which objects (e.g., individual cells) are classified using spectral and shape characteristics. All cells are morphometrically analyzed for background (portion of the digital image that is not occupied by tissue), cytoplasm (amorphous pink area that surrounds an epithelial nucleus), nuclei (round objects surrounded by cytoplasm), spectral properties (color, brightness), and shape properties (length, width, compactness, and density); a mean for each parameter will be determined and normality defined as one standard deviation within the mean. Using this technique one can objectively quantitate the number and types of tumor and/or normal cells present within a give tumor.
In short, we envision that the field will evolve in such a way as to move away from morphology-alone based categorization and more towards integration of quantitative morphometrics and molecular parametrics (see ). This will undoubtedly prove a difficult transition, since it will require breaking from the past norms. However we believe that it must be done. Some might say that this is unrealistic and unreasonable. To quote Bernard Shaw, “The reasonable man adapts himself to the world; the unreasonable man persists in trying to adapt the world to himself. Therefore all progress depends on the unreasonable man.”
Timeline of MFH highlighting critical trends past, present, and future. Please see text for details.
Key issues – 8–10 bullet points summarizing the review
- In depth understanding of the biology of different mesenchymal tumor types is lacking, hindering our treatment options.
- Murray and Stout characterize MFH and postulate that pleomorphic soft tissue tumors arise from histiocytes capable of fibroblastic transformation, the so-called “facultative fibroblast.”
- MFH sub-divided into five subtypes:: (1) storiform-pleomorphic, (2) myxoid (myxofibrosarcoma), (3) giant cell (malignant giant cell tumor of soft parts), (4) inflammatory, and (5) angiomatoid.
- Concerns of MFH being a) a diagnosis of exclusion or b) a common morphological endpoint of many advanced tumors coupled with advances in diagnosis leads to re-classification of MFH into high grade undifferentiated pleomorphic sarcomas.
- Gene expression profiling and functional analysis demonstrates that mesenchymal stem cells may be the precursors of MFH.
- Epigenetic marking may be able to discriminate undifferentiated versus differentiated.
- Differentiation therapy may be able to promote maturation of MFH into well differentiated tumors thus dramatically changing the prognosis of patients with the disease.
- Further advances will depend on our ability to move beyond morphology-based pathology towards molecular pathology.