Overexpression of transcription factor 3 in alveolar soft part sarcoma(ASPS) results in upregulation of cell proliferation pathways. No standard treatment algorithm exists for ASPS; multikinase inhibitors[tyrosine kinase inhibitor (TKI)] and immune checkpoint inhibitors (ICI) have shown clinical benefit. To date, no studies have reported on management strategies or sequencing of therapy. We evaluated ASPS treatment patterns and responses in an experimental therapeutics clinic. Genomic and morphoproteomic analysis was performed to further elucidate novel targets. We retrospectively reviewed patients with ASPS treated on clinical trials. Demographic and clinical next-generation sequencing (NGS) profiles were collected. AACR GENIE database was queried to further evaluate aberrations in ASPS. Morphoproteomic analysis was carried out to better define the biology of ASPS with integration of genomic and proteomic findings. Eleven patients with ASPS were identified; 7 received NGS testing and mutations in CDKN2A (n = 1) and hepatocyte growth factor (n = 1) were present. Ten patients were treated with TKIs with stable disease as best response and 4 patients with ICI (three partial responses). Within GENIE, 20 patients were identified harboring 3 called pathogenic mutations. Tumor mutation burden was low in all samples. Morphoproteomic analysis confirmed the expression of phosphorylated c-Met. In addition, fatty acid synthase and phosphorylated-STAT3 were detected in tumor cell cytoplasm and nuclei. Patients with ASPS have a quiescent genome and derive clinical benefit from VEGF-targeting TKIs. Morphoproteomic analysis has provided both additional correlative pathways and angiogenic mechanisms that are targetable for patients with ASPS. Our study suggests that sequential therapy with TKIs and immune checkpoint inhibitors is a reasonable management strategy.

Alveolar soft part sarcoma (ASPS) is an exceptionally rare tumor of uncertain mesenchymal origin accounting for only 1% of all soft-tissue sarcomas (STS). Contrary to the moniker “alveolar,” the tissue of origin is unknown. Instead, the histopathologic appearance of central necrosis and partitions of connective tissue give the appearance of alveoli (1, 2). ASPS is driven by the fusion of der(17)t(X;17) (p11;q25), which creates the characteristic ASPSCR1-TFE3 fusion, resulting in significant nuclear overexpression of transcription factor 3 (3). The ASPSCR1-TFE3 fusion causes upregulation of transcripts involved in angiogenesis and proliferation among other pathways (Fig. 1; ref. 4). For patients with metastatic disease, the median survival is over 3 years with median progression-free survival between 4 and 12 months. The most frequent sites of metastasis are lung, bone, and brain (5–7). This indolent disease course is paramount in understanding and interpreting any trial results. Chemotherapy does not have activity in this disease (8), and for decades the standard-of-care was surgical resection including metastatectomy (2). The above mentioned upregulation of angiogenesis transcripts provided evidence for using tyrosine kinase inhibitors (TKI) directed at VEGF. Clinical trials using TKIs, such as, sunitinib (9), cediranib (10), pazopanib (11, 12), and crizotinib (11), have demonstrated activity and have shown clinical responses. Importantly, cediranib performed favorably against placebo showing a 21% response rate versus 0% in placebo with a corresponding progression-free survival of 10.8 months compared with 3.7 months with placebo (13). Combinations of TKIs have been proposed and evaluated in STS (14), but have never been specifically investigated in ASPS. Beyond TKIs, immune checkpoint inhibitors have also shown significant activity in ASPS including near complete responses. This data largely hinges on case reports and subanalysis of larger trials including the phase II trial of axitinib with pembrolizumab for STSs (15–18). This trial was open to all patients with STS, but over a third of all patients enrolled had ASPS. With two exceptions, only patients with ASPS had documented partial responses. In patients with ASPS, the response rate was 54.5% documenting a clear sensitivity of ASPS to checkpoint blockade. To date, no studies have reported on management patterns or sequencing of therapy. No standard-of-care treatment algorithm is available for the treatment of ASPS and these patients are regularly referred to our phase I clinic. It is with this key factor in mind that we decided to evaluate treatment patterns and responses to therapy in a precision medicine and experimental therapeutics clinic.

Figure 1.

A and B, Proposed mechanism of ASPS tumorgenesis with potential downstream targets of the ASPSCR1-TFE3 fusion. The TFE3 transcription factor is postuled to activate upstream transcription of receptor tyrosine kinases, most notably MET. This causes downstream activation of the MAPK and the PI3K/AKT pathways. Inhibition of these targets is the proposed antitumor mechanism of sunitinib and similar receptor TKIs. The inhibition of VEGF may play a secondary antitumor role, but does not directly involve manipulation of downstream targets of the fusion protein.

Figure 1.

A and B, Proposed mechanism of ASPS tumorgenesis with potential downstream targets of the ASPSCR1-TFE3 fusion. The TFE3 transcription factor is postuled to activate upstream transcription of receptor tyrosine kinases, most notably MET. This causes downstream activation of the MAPK and the PI3K/AKT pathways. Inhibition of these targets is the proposed antitumor mechanism of sunitinib and similar receptor TKIs. The inhibition of VEGF may play a secondary antitumor role, but does not directly involve manipulation of downstream targets of the fusion protein.

Close modal

We conducted a retrospective review of patients with ASPS treated on clinical trials at the MD Anderson Clinical Department of Investigational Cancer Therapeutics (Houston, TX; phase I Clinical Trials Program) between 2009 and 2017. Demographic information was collected, including diagnosis, age, sex, date of first dose on trial, date of progression, best response by RECIST criteria, and if applicable, date of death and clinical next-generation sequencing (NGS) profiles performed in a Clinical Laboratory Improvement Amendments–certified environment. AACR GENIE database was queried to further evaluate mutations in other patients with ASPS (19). Data were interpreted for potential actionability using the Drug-Gene Interaction Database (20) and OncoKB (21). Investigational therapy on each clinical trial was done with approval of the MD Anderson Cancer Center Institutional Review Board. Morphoproteomic analysis (22, 23) was performed on one of the patient's specimens with a genomically (positive for ASPSCR1-TFE3 fusion) and histopathologically confirmed diagnosis of ASPS in this phase I Clinical Trial. Specifically, phosphorylated (p)-c-Met (Tyr1234/1235) [rabbit mAbs (Cell Signaling Technology)], fatty acid synthase (FAS, Cell Signaling Technology), and signal transducer and activator of transcription (STAT3), phosphorylated on tyrosine 705 (Santa Cruz Biotechnology) were the probes utilized for IHC staining.

Ethics approval and consent to participate

This retrospective review was approved by The University of Texas MD Anderson Cancer Center Institutional Review Board. All patients on clinical trials signed informed consent according to institutional standards.

Consent for publication

All authors have consented for the manuscript to be published. Consent to utilize patient information in Fig. 2 was obtained.

Figure 2.

Types and durations of therapies received by patients with ASPS. Most patients received upfront VEGF-targeted multikinase therapy. Immunotherapy was introduced late in the course of disease, likely related to entry of these agents into the clinic. Some patients had long intervals of stability off therapy representing the natural history of this disease.

Figure 2.

Types and durations of therapies received by patients with ASPS. Most patients received upfront VEGF-targeted multikinase therapy. Immunotherapy was introduced late in the course of disease, likely related to entry of these agents into the clinic. Some patients had long intervals of stability off therapy representing the natural history of this disease.

Close modal

Availability of data and material

Data sharing is not available for the patient information to ensure confidentiality.

AACR GENIE Data available at: http://genie.cbioportal.org/

We identified 11 patients with ASPS in our dataset. The median age was 21 years (range, 14–37 years) with a female predominance (F:M, 8:3). Five patients (45%) died, with overall survival durations of 10, 12, 15, 58, and 70 months. Three patients (27%) were lost to follow-up, with times of 3, 6, and 19 years. The 3 patients who were still being followed had been diagnosed 10, 11, and 12 years previously. Among all patients, the most common primary tumor site was the lower extremities (n = 7; 64%). The metastatic sites were almost exclusively the brain (n = 5; 45%) and lungs (n = 11; 100%), although one patient had liver metastasis. Eight patients presented with primary metastatic disease, and 3 developed metastases after initial therapy for curative intent. Among the 7 patients who underwent NGS testing, only two mutations were detected: CDKN2A mutation (n = 1) and hepatocyte growth factor (HGF) amplification (n = 1). Ten (91%) patients were enrolled on at least one trial that included TKI-based therapy with either pazopanib (N = 3), vandetanib (n = 4), or bevacizumab (n = 3). The best response achieved was stable disease in 9 patients on a VEGF inhibitor for a median of 12-month duration (Fig. 2). The patient with HGF amplification achieved stable disease for 28 months with multikinase TKI (pazopanib) and Histone deacetylase inhibitor (vorinostat) combination. Another patient achieved stable disease for 24 months on a combination of metformin and temsirolimus. Four patients (40%) were treated with checkpoint immunotherapy targeting the PD-1/PD-L1 axis. Three patients experienced a partial response, and 1 had stable disease as the best response, resulting in an overall response rate to immunotherapy of 75% (Fig. 3). One patient treated with PD-1/PD-L1–directed therapy had a sustained response for 8 months after stopping therapy. All therapies were given sequentially, and no patients received combination TKI and immunotherapy. Within the GENIE database, another 20 patients were identified (Table 1). There were 40 unique cancer-associated genes mutated among the 20 patients. No pathway stood out as recurrently mutated or activated, but 16 aberrant genes are potentially actionable. The majority of patients had one mutation or less (11 patients, 55%). Patients had increasing number of mutations with age. More than half (4/7, 57% patients) under the age of 25 had no potentially actionable mutation. Importantly, almost all mutations are variants of unknown significance with the exception of RB, PTEN, and PPP2R1A. The mutational burden was low with all patients having less than 20% of the genome altered. Copy-number alterations were rare and involved amplification of oncogenes and deletion of tumor suppressors. Morphoproteomic analysis confirmed the strong cytoplasmic expression (1–3+ on a scale of 0–3+) of both p-c-Met (Tyr1234/1235) and FAS and of p-STAT3 (Tyr705) in the nuclei (up to 3+) in the tumor cells of ASPS (Fig. 4).

Figure 3.

Top, patient with ASPS who achieved partial response after treatment with PD-1 axis–targeting therapy. Bottom, another patient with ASPS who achieved partial response after treatment with PD-1 axis–targeting therapy.

Figure 3.

Top, patient with ASPS who achieved partial response after treatment with PD-1 axis–targeting therapy. Bottom, another patient with ASPS who achieved partial response after treatment with PD-1 axis–targeting therapy.

Close modal
Table 1.

Potentially actionable genomic alterations identified in 20 patients with ASPS sequenced through the AACR GENIE project.

GeneNo. of mutationAmino acid changeFrequencyPredicted pathogenicClinically actionableaPathway
KMT2D 3 M1098I; R3539Q; Q4557P 15.80% No Yes Histone modification 
ERCC5 2 Q680R; G1099A 11.80% No Yes DNA repair 
PIK3CA 2 V101L; V196I 10.00% No Yes PI3K 
TOP1 1 S97F 7.10% No Yes Topoisomerase 
IRS2 1 E1009D 7.10% No Yes Insulin receptor 
POLE 1 A1629V 6.30% Yes Yes DNA polymerase 
NOTCH3 1 E1725D 5.90% No Yes Transcription factor 
ARAF 1 P216L 5.30% No Yes MAPK 
ATRX 1 G1712V 5.30% No Yes Tumor suppressor 
AXL 1 T797I 5.30% No Yes Jak/Stat 
CCND2 1 R165C 5.30% No Yes Cell-cycle 
NTRK3 1 Q586K 5.30% No Yes Tyrosine kinase 
ATM 1 Y1124F 5.00% No Yes Tumor suppressor 
KDR 1 L31P 5.00% No Yes VEGF 
NOTCH2 1 C364S 5.00% No Yes Transcription factor 
PTEN 1 Y68H 5.00% Yes Yes Tumor suppressor 
MTAP I78M 33.30% No No  
WAS A418S 33.30% No No  
ABCB11 A1283V 33.30% No No  
DCLRE1C E221G 33.30% No No  
DIS3L2 Splice_Region 33.30% No No  
BCORL1 I1022T; G1325C 28.60% No No  
CUX1 M551I 20.00% No No  
SETBP1 R625Q 20.00% No No  
FANCI R451T 20.00% No No  
ETV4 G174S 14.30% No No  
ZNF217 E209K 14.30% No No  
TP53 R196P; N239D 10.00% No No  
INPP4B P17R 7.10% No No  
FAT1 M220L 6.30% No No  
RECQL4 E9K 6.30% No No  
PMS1 D397Y 5.90% No No  
TMPRSS2 Splice_Region 5.90% No No  
PPP2R1A S303Pfs*19 5.60% Yes No  
DICER1 I829S 5.60% No No  
ARID1B R1911K; A329_G330insR 5.60% No No  
CBL R835W 5.30% No No  
SOCS1 V45_P46insRS 5.30% No No  
ARID2 K304R 5.30% No No  
RB1 V654Cfs*4 5.00% Yes No  
GeneNo. of mutationAmino acid changeFrequencyPredicted pathogenicClinically actionableaPathway
KMT2D 3 M1098I; R3539Q; Q4557P 15.80% No Yes Histone modification 
ERCC5 2 Q680R; G1099A 11.80% No Yes DNA repair 
PIK3CA 2 V101L; V196I 10.00% No Yes PI3K 
TOP1 1 S97F 7.10% No Yes Topoisomerase 
IRS2 1 E1009D 7.10% No Yes Insulin receptor 
POLE 1 A1629V 6.30% Yes Yes DNA polymerase 
NOTCH3 1 E1725D 5.90% No Yes Transcription factor 
ARAF 1 P216L 5.30% No Yes MAPK 
ATRX 1 G1712V 5.30% No Yes Tumor suppressor 
AXL 1 T797I 5.30% No Yes Jak/Stat 
CCND2 1 R165C 5.30% No Yes Cell-cycle 
NTRK3 1 Q586K 5.30% No Yes Tyrosine kinase 
ATM 1 Y1124F 5.00% No Yes Tumor suppressor 
KDR 1 L31P 5.00% No Yes VEGF 
NOTCH2 1 C364S 5.00% No Yes Transcription factor 
PTEN 1 Y68H 5.00% Yes Yes Tumor suppressor 
MTAP I78M 33.30% No No  
WAS A418S 33.30% No No  
ABCB11 A1283V 33.30% No No  
DCLRE1C E221G 33.30% No No  
DIS3L2 Splice_Region 33.30% No No  
BCORL1 I1022T; G1325C 28.60% No No  
CUX1 M551I 20.00% No No  
SETBP1 R625Q 20.00% No No  
FANCI R451T 20.00% No No  
ETV4 G174S 14.30% No No  
ZNF217 E209K 14.30% No No  
TP53 R196P; N239D 10.00% No No  
INPP4B P17R 7.10% No No  
FAT1 M220L 6.30% No No  
RECQL4 E9K 6.30% No No  
PMS1 D397Y 5.90% No No  
TMPRSS2 Splice_Region 5.90% No No  
PPP2R1A S303Pfs*19 5.60% Yes No  
DICER1 I829S 5.60% No No  
ARID1B R1911K; A329_G330insR 5.60% No No  
CBL R835W 5.30% No No  
SOCS1 V45_P46insRS 5.30% No No  
ARID2 K304R 5.30% No No  
RB1 V654Cfs*4 5.00% Yes No  

Note: Bolded items are cancer associated potentially actionable genes in the clinic.

aClinical actionability determined at the time of clinical trial enrollment.

Figure 4.

Morphoproteomic analysis in the patient with ASPS depicts the hematoxylin and eosin (H&E; A) and up to 3+ brown-chromogenic expression of p-c-Met (Tyr 1234/1235) and fatty acid synthase (FAS) in the cytoplasmic compartment of the tumor cells (B and C, respectively) and p-STAT3 (Tyr 705) with variable expression up to 3+ translocated to the tumoral nuclei (D) on a scale of 0–3+ (original magnifications ×200).

Figure 4.

Morphoproteomic analysis in the patient with ASPS depicts the hematoxylin and eosin (H&E; A) and up to 3+ brown-chromogenic expression of p-c-Met (Tyr 1234/1235) and fatty acid synthase (FAS) in the cytoplasmic compartment of the tumor cells (B and C, respectively) and p-STAT3 (Tyr 705) with variable expression up to 3+ translocated to the tumoral nuclei (D) on a scale of 0–3+ (original magnifications ×200).

Close modal

Despite the small number of patients in our retrospective study, this represents a unique series of patients with ASPS who were enrolled on multiple clinical trials. We observed significant activity across clinical trials and a variety of agents. Previous studies have described partial responses with VEGF multikinase targeting TKIs (Cediranib, sunitinib, pazopanib), but we did not observe any such responses. This is likely because of the small number of patients in this study and the variation in actual agents used. Instead, patients did derive substantial clinical benefit from VEGF-targeting therapy in the form of prolonged stable disease. One important concept emerged from the recent publication by Wilky and colleagues (18): the long duration time to response, over 25 weeks before seeing a partial response. This knowledge was not available to the treating physicians involved in the care of these patients and may perhaps explain why some patients were transitioned from their therapy relatively early. Had patients stayed on therapy, better responses may have been seen.

While the concept of stability as an endpoint in an indolent disease is debatable, we know from prior studies that overall survival in untreated patients with metastatic disease is between 3 and 4 years (5, 6). In our study, 8 patients had overall survival duration far longer than 3 years. This is especially impressive as the phase I clinic is naturally a referral of last resort for most patients and represents a heavily pretreated cohort. In addition, one placebo-controlled study of cediranib in ASPS showed that a progression-free survival advantage (10.8 months for cediranib vs. 3.7 months for placebo) resulted in an overall survival advantage at 12 months (96% for cediranib vs. 64% for placebo) (13). This suggests that even in an indolent disease such as ASPS, prolonged stable disease is beneficial to patient survival. In our experience, treatment with VEGF-targeted therapy is worthwhile even if disease stability is the overall goal. Our study was not powered to detect differences between therapeutic regimens because of small numbers of patients and we cannot recommend one particular agent over another. However, based on intrapatient observation, we do feel that combinations of drugs performed better than single agents, with acceptable toxicity. Future studies combining a VEGF-directed TKI with another targeted agent in ASPS are of interest. In that regard, morphoproteomic analysis provides the following correlative insights into the biology of ASPS: (i) ASPL-TFE 3 fusion protein in ASPS binds to the MET promoter and induces the expression of c-Met tyrosine kinase and the finding of phosphorylated c-Met indicates that it has been activated by HGF, its ligand (24); (ii) FAS expression represents a correlate to c-Met pathway signaling because inhibition of FAS posttranscriptionally downregulates c-Met expression (25); and (iii) the constitutive activation of the signal transducer and activation of transcription (STAT)3 pathway in the tumor cells in the form of phosphorylation of STAT3 on tyrosine 705 with translocation to the nucleus represents a potential autocrine mechanism in providing HGF, the ligand for c-Met given the role of c-src-STAT3 pathway activation as a transcriptional activator of HGF (26, 27) and further correlates with the previous demonstration of activation of platelet-derived growth factor receptor signaling in ASPS (9, 28), which in turn is consistent with the activation of p-STAT3 (Tyr 705) via the src-STAT3 pathway (29). These observations provide therapeutic targets for relatively low toxicity agents in patients with ASPS, such as crizotinib to interfere with the HGF/c-Met signaling pathway and angiogenesis (11), pazopanib to participate in the inhibition of angiogenesis by VEGF (30, 31), and metformin to downregulate FAS and to interfere in c-Met–driven tumorigenesis (32, 33) and prevent the phosphorylation/activation of the STAT3 pathway (34, 35). Interestingly, the role of metformin is complex with different concentrations in the preclinical studies that support its mechanism of action [5–10 mmol/L metformin (32); 0.5–2 mmol/L (33), and 1.25–5 mmol/L metformin (34)]. These are quite nonphysiologic exposures to metformin (1.8 g dose in human gives ∼30 μmol/L Cmax). Indeed, the predominant preclinical murine models of anticancer activity of metformin are possibly a guesstimate of higher doses of metformin administration in human studies versus submillimolar treatment of cells in culture, which is a caveat in interpretation of preclinical murine metformin studies (36).

One of the longest periods of stable disease (28 months) on therapy was observed in a patient with HGF amplification. High HGF expression has previously been reported in ASPS. Importantly, this correlated with c-Met phosphorylation and activation (37). The patient was treated with pazopanib, which is considered a VEGF inhibiting TKI, but has broad activity against other kinases including c-Met (38). This highlights the possibility that TKI activity in ASPS goes beyond simple VEGF inhibition. Other authors have similarly proposed that TKIs with multikinase activity are more efficacious in ASPS (2), and our experience supports this hypothesis. A similar duration of stable disease (22 months) was seen in a patient on a phase II trial of pazopanib in patients with ASPS, but limited data are available regarding the patient's genomics (12).

In contrast to VEGF-targeted therapy, immunotherapy shows a clear signal of response in patients with ASPS. In a disease where stability with periods of progression is the norm, true partial responses are unusual and provocative. Such findings have previously been reported either as individual cases (15) or as a subanalysis of a larger study (16). At the 2018 Connective Tissue Oncology Society meeting, Geraldine O'Sullivan Coyne presented the first stage of the phase II study of atezolizumab in ASPS. Eighteen patients were evaluable with 7 observed partial responses (39%), without unexpected toxicity (39). The use of metformin as suggested by morphoproteomic analysis is relevant in this regard because metformin reduces PD-L1 by endoplasmic reticulum-associated degradation (40).

Clinical-grade DNA hybrid capture–targeted exome sequencing did not identify readily actionable cooccurring mutations in our patients. We investigated this further by analyzing patients with ASPS sequenced in the AACR GENIE database. We did find 16 potentially actionable aberrant genes. However, the association between increasing age and number of mutations suggests that at least some of these aberrations are passengers accumulated over time, rather than true driver mutations. This is further bolstered by the fact that almost all mutations are variants of unknown significance. This phenomenon of increasing mutations with age has previously been documented (41). In addition, sequencing data support a low tumor mutational burden in this disease. Unfortunately, genomic profiling does not appear to answer why multikinase VEGF directed or immunotherapy works in patients with ASPS. One of the major limitations of this manuscript is lack of comprehensive immunoprofiling. Future studies including genomic, proteomic, and immunoprofiling are underway. This may potentially unravel resistance and response mechanisms to immune checkpoint inhibitors. From our study, it is clear that genomic mutations and copy-number variations do not hold the key to understanding this disease. Further studies should focus on the oncogenic mechanism of the ASPS-TFE3 gene fusion perhaps utilizing next-generation–based RNA-sequencing and morphoproteomics to unlock the mystery of this nebulous and mercurial disease.

Patients with ASPS have a quiescent genome and derive clinical benefit from VEGF-targeting multikinase agents. In light of the frequently indolent and variable course of ASPS, stable disease is a difficult endpoint to interpret. In contrast, immune checkpoint blockade yields clear partial responses. No guidelines exist for management of patients with ASPS, except to avoid traditional chemotherapy. Our study suggests that sequential therapy with TKIs disrupting not only VEGF, but other signaling pathways demonstrated by morphoproteomics is a reasonable management strategy. In line with other reports, prolonged treatment may be required to see significant clinical activity. For patients in whom a true response is needed, immunotherapy targeting the PD-1/PD-L1 axis is recommended. Above all, enrollment in clinical trials is paramount.

A.P. Conley is a consultant at Bayer, Deciphera, and Genentech. D.S. Hong is a consultant at Alpha Insights, Axiom, Janssen, Merrimack, Medscape, Numab, Pfizer, Seattle Genetics, Takeda, Trieza, Adaptimmune, Baxter, Bayer, Genentech, GLG, Group H, Guidepoint Global, Infinity, reports receiving a commercial research grant from Abbvie, Adaptimmune, Genmab, Ignyta, Infinity, Kite, Kyowa, Lilly, LOXO, Merck, Medimmune, Mirati, Amgen, MiRNA, Molecular Templates, Mologen, NCI-CTEP, Novartis, Pfizer, Seattle Genetics, Takeda, AstraZeneca, Bayer, BMS, Daiichi-Sanko, Eisai, Fate Therapeutics, Genentech, and reports receiving other commercial research support from LOXO, MiRNA, ASCO, AACR, SITC, Genmab, has ownership interest (including patents) in Molecular Match, OncoResponse, and Presagia. A. Naing reports receiving a commercial research grant from NCI, EMD Serono, Regeneron, Merck, BMS, Pfizer, CytomX Therapeutics, Neon Therapeutics, Calithera Biosciences, TopAlliance Biosciences, Eli Lilly, Kymab, MedImmune, PsiOxus, Immune Deficiency Foundation, Healios Onc. Nutrition, Atterocor, Amplimmune, ARMO BioSciences, Karyopharm Therapeutics, Incyte, Novartis, has received speakers bureau honoraria from CytomX Therapeutics and Novartis, and has provided expert testimony for ARMO BioSciences (travel and accommodation). C.E. Herzog is a member, data monitoring committee at Merck, Sharp, and Dome and reports receiving a commercial research grant from Roche Genentech and Array Biopharm. S. Patel is a consultant at Novartis, Epizyme, Daiichi Sankyo, Dova, Bayer and reports receiving a commercial research grant from Blueprint Medicines. V. Subbiah is a consultant/advisory board member at LOXO Oncology/Eli Lilly, Helsinn, R-Pharma US, Incyte, QED, Novartis, Medimmune and reports receiving a commercial research grant from LOXO Oncology/Eli Lilly, Blueprint Medicines, Fujifilm, Pharmamar, D3, Pfizer, Multivir, Amgen, ABBVIE, Agensys, Boston Biomedical, Idera, Turning Point therapeutics, Exelixis, Inhibrx, Altum, Medimmune, Dragonfly Therapeutics, Takeda, Roche/Genentech, Novartis, Bayer, GSK, Nanocarrier, Berghealth, Incyte, and Northwest Biotherapeutics. No potential conflicts of interest were disclosed by the other authors.

Conception and design: R. Groisberg, A.J. Lazar, S. Patel, V. Subbiah

Development of methodology: R. Groisberg, S. Patel, R.E. Brown, V. Subbiah

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): R. Groisberg, A.P. Conley, A.J. Lazar, D.S. Hong, A. Naing, C.E. Herzog, N. Somaiah, M.A. Zarzour, S. Patel, V. Subbiah

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): R. Groisberg, J. Roszik, A.P. Conley, A.J. Lazar, A. Naing, S. Patel, V. Subbiah

Writing, review, and/or revision of the manuscript: R. Groisberg, J. Roszik, A.P. Conley, A.J. Lazar, D.E. Portal, D.S. Hong, A. Naing, C.E. Herzog, N. Somaiah, S. Patel, R.E. Brown, V. Subbiah

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): R. Groisberg, A.J. Lazar, V. Subbiah

Study supervision: R. Groisberg, V. Subbiah

Other (developed morphoproteomics as a discipline and have contributed to the writing, review and revision of the manuscript): R.E. Brown

The University of Texas MD Anderson Cancer Center is supported by the NIH Cancer Center Support Grant CA016672. V. Subbiah acknowledges the Shannon Wilkes Sarcoma Research funds. This work was supported in part by Cancer Prevention Research Institute of Texas Grant RP110584 and National Center for Advancing Translational Sciences Grant UL1 TR000371 (Center for Clinical and Translational Sciences). We thank the patients and their families for enrolling in clinical trials.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Christopherson
WM
,
Foote
FW
,
Stewart
FW
. 
Alveolar soft-part sarcomas. Structurally characteristic tumors of uncertain histogenesis
.
Cancer
1952
;
5
:
100
11
.
2.
Paoluzzi
L
,
Maki
RG
. 
Diagnosis, prognosis, and treatment of alveolar soft-part sarcoma: a review
.
JAMA Oncol
2019
;
5
:
254
60
.
3.
Ladanyi
M
,
Lui
MY
,
Antonescu
CR
,
Krause-Boehm
A
,
Meindl
A
,
Argani
P
, et al
The der(17)t(X;17)(p11;q25) of human alveolar soft part sarcoma fuses the TFE3 transcription factor gene to ASPL, a novel gene at 17q25
.
Oncogene
2001
;
20
:
48
57
.
4.
Stockwin
LH
,
Vistica
DT
,
Kenney
S
,
Schrump
DS
,
Butcher
DO
,
Raffeld
M
, et al
Gene expression profiling of alveolar soft-part sarcoma (ASPS)
.
BMC Cancer
2009
;
9
:
22
.
5.
Lieberman
PH
,
Brennan
MF
,
Kimmel
M
,
Erlandson
RA
,
Garin-Chesa
P
,
Flehinger
BY
. 
Alveolar soft-part sarcoma. A clinico-pathologic study of half a century
.
Cancer
1989
;
63
:
1
13
.
6.
Portera
CA
 Jr
,
Ho
V
,
Patel
SR
,
Hunt
KK
,
Feig
BW
,
Respondek
PM
, et al
Alveolar soft part sarcoma
.
Cancer
2001
;
91
:
585
91
.
7.
Flores
RJ
,
Harrison
DJ
,
Federman
NC
,
Furman
WL
,
Huh
WW
,
Broaddus
EG
, et al
Alveolar soft part sarcoma in children and young adults: a report of 69 cases
.
Pediatr Blood Cancer
2018
;
65
:
e26953
.
8.
Reichardt
P
,
Lindner
T
,
Pink
D
,
Thuss-Patience
PC
,
Kretzschmar
A
,
Dorken
B
. 
Chemotherapy in alveolar soft part sarcomas. What do we know?
Eur J Cancer
2003
;
39
:
1511
6
.
9.
Stacchiotti
S
,
Negri
T
,
Zaffaroni
N
,
Palassini
E
,
Morosi
C
,
Brich
S
, et al
Sunitinib in advanced alveolar soft part sarcoma: evidence of a direct antitumor effect
.
Ann Oncol
2011
;
22
:
1682
90
.
10.
Kummar
S
,
Allen
D
,
Monks
A
,
Polley
EC
,
Hose
CD
,
Ivy
SP
, et al
Cediranib for metastatic alveolar soft part sarcoma
.
J Clin Oncol
2013
;
31
:
2296
302
.
11.
Schoffski
P
,
Wozniak
A
,
Kasper
B
,
Aamdal
S
,
Leahy
MG
,
Rutkowski
P
, et al
Activity and safety of crizotinib in patients with alveolar soft part sarcoma with rearrangement of TFE3: European organization for research and treatment of cancer (EORTC) phase II trial 90101 ‘CREATE'
.
Ann Oncol
2018
;
29
:
758
65
.
12.
Kim
M
,
Kim
TM
,
Keam
B
,
Kim
YJ
,
Paeng
JC
,
Moon
KC
, et al
A phase II trial of pazopanib in patients with metastatic alveolar soft part sarcoma
.
Oncologist
2019
;
24
:
20
e9
.
13.
Judson
IR
,
Morden
JP
,
Leahy
MG
,
Bhadri
V
,
Campbell-Hewson
Q
,
Cubedo
R
, et al
Activity of cediranib in alveolar soft part sarcoma (ASPS) confirmed by CASPS (cediranib in ASPS), an international, randomised phase II trial (C2130/A12118)
.
J Clin Oncol
2017
;
35
:
11004
.
14.
Dembla
V
,
Groisberg
R
,
Hess
K
,
Fu
S
,
Wheler
J
,
Hong
DS
, et al
Outcomes of patients with sarcoma enrolled in clinical trials of pazopanib combined with histone deacetylase, mTOR, Her2, or MEK inhibitors
.
Sci Rep
2017
;
7
:
15963
.
15.
Conley
AP
,
Trinh
VA
,
Zobniw
CM
,
Posey
K
,
Martinez
JD
,
Arrieta
OG
, et al
Positive tumor response to combined checkpoint inhibitors in a patient with refractory alveolar soft part sarcoma: a case report
.
J Glob Oncol
2018
;
4
:
1
6
.
16.
Groisberg
R
,
Hong
DS
,
Behrang
A
,
Hess
K
,
Janku
F
,
Piha-Paul
S
, et al
Characteristics and outcomes of patients with advanced sarcoma enrolled in early phase immunotherapy trials
.
J Immunother Cancer
2017
;
5
:
100
.
17.
Lewin
J
,
Davidson
S
,
Anderson
ND
,
Lau
BY
,
Kelly
J
,
Tabori
U
, et al
Response to immune checkpoint inhibition in two patients with alveolar soft-part sarcoma
.
Cancer Immunol Res
2018
;
6
:
1001
7
.
18.
Wilky
BA
,
Trucco
MM
,
Subhawong
TK
,
Florou
V
,
Park
W
,
Kwon
D
, et al
Axitinib plus pembrolizumab in patients with advanced sarcomas including alveolar soft-part sarcoma: a single-centre, single-arm, phase 2 trial
.
Lancet Oncol
2019
;
20
:
837
48
.
19.
Vuzman
D
,
Powers
W
,
Huang
X
,
Sun
R
,
Eifert
C
,
Cingolani
P
, et al
Tumor mutation burden derived from large NGS panel as biomarker for immunotherapy response
.
J Clin Oncol
2017
;
35
:
e23077
.
20.
Cotto
KC
,
Wagner
AH
,
Feng
Y-Y
,
Kiwala
S
,
Coffman
AC
,
Spies
G
, et al
DGIdb 3.0: a redesign and expansion of the drug–gene interaction database
.
Nucleic Acids Res
2018
;
46
:
D1068
D73
.
21.
Chakravarty
D
,
Gao
J
,
Phillips
S
,
Kundra
R
,
Zhang
H
,
Wang
J
, et al
OncoKB: a precision oncology knowledge base
.
JCO Precis Oncol
2017
;
1
.
DOI: 10.1200/PO.17.00011
.
22.
Brown
RE
. 
Morphoproteomics: exposing protein circuitries in tumors to identify potential therapeutic targets in cancer patients
.
Expert Rev Proteomics
2005
;
2
:
337
48
.
23.
Brown
RE
. 
Morphogenomics and morphoproteomics: a role for anatomic pathology in personalized medicine
.
Arch Pathol Lab Med
2009
;
133
:
568
79
.
24.
Tsuda
M
,
Davis
IJ
,
Argani
P
,
Shukla
N
,
McGill
GG
,
Nagai
M
, et al
TFE3 fusions activate MET signaling by transcriptional up-regulation, defining another class of tumors as candidates for therapeutic MET inhibition
.
Cancer Res
2007
;
67
:
919
29
.
25.
Uddin
S
,
Hussain
AR
,
Ahmed
M
,
Bu
R
,
Ahmed
SO
,
Ajarim
D
, et al
Inhibition of fatty acid synthase suppresses c-Met receptor kinase and induces apoptosis in diffuse large B-cell lymphoma
.
Mol Cancer Ther
2010
;
9
:
1244
55
.
26.
Zhang
YW
,
Wang
LM
,
Jove
R
,
Vande Woude
GF
. 
Requirement of Stat3 signaling for HGF/SF-Met mediated tumorigenesis
.
Oncogene
2002
;
21
:
217
26
.
27.
Hung
W
,
Elliott
B
. 
Co-operative effect of c-Src tyrosine kinase and Stat3 in activation of hepatocyte growth factor expression in mammary carcinoma cells
.
J Biol Chem
2001
;
276
:
12395
403
.
28.
Stacchiotti
S
,
Tamborini
E
,
Marrari
A
,
Brich
S
,
Rota
SA
,
Orsenigo
M
, et al
Response to sunitinib malate in advanced alveolar soft part sarcoma
.
Clin Cancer Res
2009
;
15
:
1096
104
.
29.
Hbibi
AT
,
Lagorce
C
,
Wind
P
,
Spano
JP
,
Des Guetz
G
,
Milano
G
, et al
Identification of a functional EGF-R/p60c-src/STAT3 pathway in colorectal carcinoma: analysis of its long-term prognostic value
.
Cancer Biomark
2008
;
4
:
83
91
.
30.
Shido
Y
,
Matsuyama
Y
. 
Advanced Alveolar soft part sarcoma treated with pazopanib over three years
.
Case Rep Oncol Med
2017
;
2017
:
3738562
.
31.
Lee
ATJ
,
Jones
RL
,
Huang
PH
. 
Pazopanib in advanced soft tissue sarcomas
.
Signal Transduct Target Ther
2019
;
4
:
16
.
32.
Wahdan-Alaswad
RS
,
Cochrane
DR
,
Spoelstra
NS
,
Howe
EN
,
Edgerton
SM
,
Anderson
SM
, et al
Metformin-induced killing of triple-negative breast cancer cells is mediated by reduction in fatty acid synthase via miRNA-193b
.
Horm Cancer
2014
;
5
:
374
89
.
33.
Zhang
C
,
Hu
J
,
Sheng
L
,
Yuan
M
,
Wu
Y
,
Chen
L
, et al
Metformin delays AKT/c-Met-driven hepatocarcinogenesis by regulating signaling pathways for de novo lipogenesis and ATP generation
.
Toxicol Appl Pharmacol
2019
;
365
:
51
60
.
34.
Liu
B
,
Fan
Z
,
Edgerton
SM
,
Deng
XS
,
Alimova
IN
,
Lind
SE
, et al
Metformin induces unique biological and molecular responses in triple negative breast cancer cells
.
Cell Cycle
2009
;
8
:
2031
40
.
35.
Deng
XS
,
Wang
S
,
Deng
A
,
Liu
B
,
Edgerton
SM
,
Lind
SE
, et al
Metformin targets Stat3 to inhibit cell growth and induce apoptosis in triple-negative breast cancers
.
Cell Cycle
2012
;
11
:
367
76
.
36.
Dowling
RJ
,
Lam
S
,
Bassi
C
,
Mouaaz
S
,
Aman
A
,
Kiyota
T
, et al
Metformin pharmacokinetics in mouse tumors: implications for human therapy
.
Cell Metab
2016
;
23
:
567
8
.
37.
Lazar
AJ
,
Lahat
G
,
Myers
SE
,
Smith
KD
,
Zou
C
,
Wang
WL
, et al
Validation of potential therapeutic targets in alveolar soft part sarcoma: an immunohistochemical study utilizing tissue microarray
.
Histopathology
2009
;
55
:
750
5
.
38.
Outani
H
,
Tanaka
T
,
Wakamatsu
T
,
Imura
Y
,
Hamada
K
,
Araki
N
, et al
Establishment of a novel clear cell sarcoma cell line (Hewga-CCS), and investigation of the antitumor effects of pazopanib on Hewga-CCS
.
BMC Cancer
2014
;
14
:
455
.
Available from:
https://www.ctos.org/Portals/0/PDF/2017%20CTOS%20Final%20Program.pdf
39.
Coyne
GOS
,
Sharon
E
,
Moore
N
,
Meehan
R
,
Takebe
N
,
Juwara
L
, et al
Phase II study of atezolizumab in patients with alveolar soft part sarcoma. Presented at: 2018 CTOS Annual Meeting; November 14-17, 2018; Rome, Italy
.
Available from:
https://www.ctos.org/Portals/0/PDF/2017%20CTOS%20Final%20Program.pdf.
40.
Cha
JH
,
Yang
WH
,
Xia
W
,
Wei
Y
,
Chan
LC
,
Lim
SO
, et al
Metformin promotes antitumor immunity via endoplasmic-reticulum-associated degradation of PD-L1
.
Mol Cell
2018
;
71
:
606
20
.
41.
Salem
ME
,
Xiu
J
,
Lenz
H-J
,
Atkins
MB
,
Philip
PA
,
Hwang
JJ
, et al
Characterization of tumor mutation load (TML) in solid tumors
.
J Clin Oncol
2017
;
35
:
11517
.