Homogenous Good Outcome in a Heterogeneous Group of Tumors: An Institutional Series of Outcomes of Superficial Soft Tissue Sarcomas

Superficial soft tissue sarcomas: 10‑year survival outcomes

Cutaneous sarcomas comprise a broad group of rare, heterogeneous mesenchymal tumours. The present report describes a single centre experience regarding the management and the outcomes of patients with superficial soft tissue sarcomas (SSTS). Key prognostic factors in predicting overall survival (OS) and local relapse-free survival were determined. Data from 66 patients with SSTS treated surgically within Edinburgh and Lothian were collected in the context of a service evaluation. Patient demographics, tumour specifics and treatment, as well as 5-year OS and local recurrence, were analysed. Kaplan-Meier analysis was applied for survival curves, and mortality rate estimation and Cox regression were used to establish independent predictors. The mean estimated OS time was 57.2 months, with a 95% CI between 55.0 and 59.5 months. The median OS time could not be estimated because there is no time point during which the survival function has a value <50%. The death risk for a person with SSTS was increased by 7.3% (odds ratio, 1.073; 95% CI, 1.012-1.138) for every additional year of life. The estimated mean local relapse time was 58.5 months, with a 95% CI between 56 and 61 months. The median local relapse time could not be estimated since there is no time point during which the local recurrence function has a value <50%. In conclusion, out of all independent variables considered, none could statistically significantly explicate local relapse recurrence time. It is important that these rare tumours are treated in the context of a multidisciplinary team with consensus guidelines to assist decision-making.

Nomograms predicting local and distant recurrence and disease-specific mortality for R0/R1 soft tissue sarcomas of the extremities

Background

Prognostic models for patients with soft tissue sarcoma (STS) of the extremities have been developed from large multi-institutional datasets with mixed results. We aimed to develop predictive nomograms for sarcoma-specific survival (SSS) and, for the first time, long-term local recurrence (LR) and distant recurrence (DR) in patients with STS of the extremities treated at our institution.

Patients and methods

Data from patients treated at Humanitas Cancer Center from 1997 to 2015 were analyzed. Variable selection was based on the clinical knowledge and multivariable regression splines algorithm. Perioperative treatments were always included in the model. Prognostic models were developed using Cox proportional hazards model, and model estimates were plotted in nomograms predicting SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. Model performance was estimated internally via bootstrapping, in terms of optimism-corrected discrimination (Harrell C-index) and calibration (calibration plots).

Results

Data on 517 patients were analyzed. At 5 and 10 years, SSS was 68.1% [95% confidence interval (CI), 63.8–72.1] and 55.6% (50.5–60.3), respectively. LR was 79.1% (95% CI, 75.3–82.4), 71.1% (95% CI, 66.7–75.1), and 66.0% (95% CI, 60.7–70.7) at 2, 5, and 10 years, respectively, whereas DR was 65.9% (95% CI, 61.6–69.9), 57.5% (95% CI, 53.0–61.8), and 52.1% (95% CI, 47.1–56.8) at 2, 5, and 10 years, respectively. SSS nomogram included age, gender, margins, tumor size, grading, and histotype. LR and DR nomograms incorporated mostly the same variables, except for age for DR; LR nomogram did not include gender but included anatomic site. The optimism-corrected C-indexes were 0.73 and 0.72 for SSS at 5 and 10 years, respectively; 0.65, 0.64, and 0.64 for LR at 2, 5, and 10 years, respectively; and 0.68 for DR at 2, 5, and 10 years. Predicted probabilities were close to the observed ones for all outcomes.

Conclusions

We developed and validated three nomograms for STS of the extremities predicting the probability of SSS at 5 and 10 years and LR and DR at 2, 5, and 10 years. By accounting for the perioperative treatment, these models allow prediction for future patients who had no perioperative treatment, thus being useful in the clinical decision-making process.

Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma

Rationale: Hypoxic regions (habitats) within tumors are heterogeneously distributed and can be widely variant. Hypoxic habitats are generally pan-therapy resistant. For this reason, hypoxia-activated prodrugs (HAPs) have been developed to target these resistant volumes. The HAP evofosfamide (TH-302) has shown promise in preclinical and early clinical trials of sarcoma. However, in a phase III clinical trial of non-resectable soft tissue sarcomas, TH-302 did not improve survival in combination with doxorubicin (Dox), possibly due to a lack of patient stratification based on hypoxic status. Therefore, we used magnetic resonance imaging (MRI) to identify hypoxic habitats and non-invasively follow therapies response in sarcoma mouse models. Methods: We developed deep-learning (DL) models to identify hypoxia, using multiparametric MRI and co-registered histology, and monitored response to TH-302 in a patient-derived xenograft (PDX) of rhabdomyosarcoma and a syngeneic model of fibrosarcoma (radiation-induced fibrosarcoma, RIF-1). Results: A DL convolutional neural network showed strong correlations (>0.76) between the true hypoxia fraction in histology and the predicted hypoxia fraction in multiparametric MRI. TH-302 monotherapy or in combination with Dox delayed tumor growth and increased survival in the hypoxic PDX model (p<0.05), but not in the RIF-1 model, which had a lower volume of hypoxic habitats. Control studies showed that RIF-1 resistance was due to hypoxia and not other causes. Notably, PDX tumors developed resistance to TH-302 under prolonged treatment that was not due to a reduction in hypoxic volumes. Conclusion: Artificial intelligence analysis of pre-therapy MR images can predict hypoxia and subsequent response to HAPs. This approach can be used to monitor therapy response and adapt schedules to forestall the emergence of resistance.

Treatment outcome of superficial leiomyosarcoma

BACKGROUND

Nonuterine leiomyosarcomas (LMS) are common extremity soft-tissue sarcomas. Deep LMS are at an increased risk for recurrence; however, few studies have focused on superficial LMS.

METHODS

We reviewed the clinicopathological features of 82 patients with a primary superficial LMS. The mean age and follow-up were 57 ± 15 and 7 ± 5 years. Depth was classified as dermal (based in the skin; n = 35, 43%) and subcutaneous (based below the dermis, above the fascia; n = 47, 57%) on the final resection specimen. Dermal cases were treated with negative margin resection, while subcutaneous tumors were evaluated by a multidisciplinary team for consideration of possible adjuvant therapy.

RESULTS

The 10-year disease-specific survival (DSS) for superficial LMS was 90% with no difference (p = .18) in the 10-year DSS between patients with dermal (100%) and subcutaneous (86%) LMS. All disease recurrences occurred in subcutaneous LMS (17% vs. 0%, p = .02) and subcutaneous tumors had a worse10-year metastatic free survival (81% vs. 100%, p = .03).

CONCLUSIONS

The results of this study suggest that dermal LMS can be managed with a negative margin resection alone. Although the prognosis for patients with subcutaneous LMS is quite favorable, there is some risk for local and distant recurrence, and such patients will benefit from multidisciplinary care.

Diagnosis and Management of Subcutaneous Soft Tissue Sarcoma

OPINION STATEMENT

The proper diagnosis and treatment planning for subcutaneous soft tissue sarcoma is very important. Soft tissue tumors can occur anywhere in the body, but if they occur subcutaneously, patients can easily notice a subcutaneous soft tissue mass. Therefore, it is possible to determine through recording, the growth speed of the mass, which is often difficult to obtain with deep-situated soft tissue masses. Palpation can also provide information about the firmness and mobility of the mass. Thus, history taking and physical examinations are informative for subcutaneous soft tissue tumors, compared to tumors that occur deeply. Because subcutaneous soft tissue tumors are easily recognized, they are often resected, without sufficient imaging analyses or thorough treatment planning. An operation performed based on such an inadequate preoperative plan is called a "whoops surgery." In the case of "whoops surgeries," subsequent radical surgery is required to remove additional areas, including hematomas that result from the initial surgery, that require a wider range of resection and soft tissue reconstruction. Therefore, as with deep-seated soft tissue tumors, it is important to conduct careful imaging examinations and make appropriate preoperative plans for subcutaneous soft tissue tumors. Subcutaneous soft tissue sarcomas often show an invasive pattern, and such tumors require a more careful assessment to prevent local recurrence after surgery. During surgery, it is necessary to remove the entire infiltration area along the fascia. Sometimes, an adequately wide excision is necessary, which is considered the minimum necessary procedure to eradicate the lesion. As noted above, clinicians who see patients with subcutaneous soft tissue tumors are encouraged to have sufficient knowledge and experience regarding the diagnosis and treatment. This article is intended for all doctors who deal with subcutaneous soft tissue tumors and focuses on essential points regarding their diagnosis and management.