The Prognostic Value of Lymphovascular Invasion in Truncal and Extremity Soft Tissue Sarcomas: An Analysis from the National Cancer Database

Tumor necrosis is an underappreciated histopathologic factor in the grading of chondrosarcoma

BACKGROUND

Cartilaginous neoplasms can be challenging to grade; there is a need to create an evidence-based rubric for grading. The goal of this study was to identify histopathologic features of chondrosarcoma that were associated with 5-year survival and to compare these to traditional patient, tumor and treatment variables.

METHODS

This was a retrospective review of all patients undergoing surgical resection of a primary chondrosarcoma with at least 2 years of follow up. All specimens were independently reviewed by two pathologists and histopathologic features scored. Univariate and multivariate analyses were performed utilizing Kaplan Meier and proportional hazards methods to identify variables associated with 5-year disease specific survival (DSS) and disease free survival (DFS).

RESULTS

We identified 51 patients with an average follow up of 49 months eligible for inclusion. 30% of tumors were low grade, 45% were intermediate grade, and 25% were high grade. In a univariate analysis considering histopathologic factors, higher tumor mitotic rate (HR 8.9, p < 0.001), tumor dedifferentiation (HR 7.3, p < 0.001), increased tumor cellularity (HR 5.8, p = 0.001), increased tumor atypia (HR 5.8, p = 0.001), LVI (HR 4.7, p = 0.04) and higher tumor necrosis (HR 3.7, p = 0.02) were all associated with worse 5-year DSS. In a multivariate analysis controlling for potentially confounding variables, higher tumor necrosis was significantly associated with disease specific survival survival (HR 3.58, p = 0.035); none of the factors were associated with DFS.

CONCLUSIONS

This study provides an evidence-based means for considering histopathologic markers and their association with prognosis in chondrosarcoma. Our findings suggest that necrosis and LVI warrant further study.

Correlative Study on the Relationship between the Expression of m6a-Related Genes and the Prognosis and Immunotherapy of Soft Tissue Sarcoma

Background

Soft tissue sarcomas (STS) are rare malignancies arising from mesenchymal tissue and interlacing ectodermal nerve tissue. Immunotherapy plays an important role in the prognosis and survival of STS patients. However, there is insufficient evidence to confirm the prognostic value of m6A-related genes and to evaluate the efficacy of immunotherapy for STS.

Methods

We analyzed 23 m6A regulators from STS samples using R software and defined the modification patterns for three STS m6A regulators. Then, we constructed the m6A scores and divided the samples into high and low subgroups. Finally, we used data from the GEO database to verify the results.

Results

We found that the m6A clusters differed in the overall survival (OS), progression-free survival (PFS), and immune infiltration rate. Additionally, the m6A score was positively correlated with the contents of activated B cells, activated dendritic cells, CD56 bright natural killer cells, helper T cells, and regulatory T cells. The group with a higher m6A score also presented higher OS and PFS rates. Regarding immunotherapy, STS patients with a high m6A score presented better results. Consistently, we found similar results in another dataset with patients that received anti-PD-1/PD-L1 therapy.

Conclusion

Our current results indicated that the m6A score can be used to assess the survival rate of STS patients and guide immunotherapy and predict its effects. The analysis of different m6A patterns of STS samples contributed to the understanding of the diversity and complexity of the tumor microenvironment (TME) and provided new ideas for the clinical development of personalized immunotherapy and prediction of the prognosis of STS patients.

Construction, validation and, visualization of a web-based nomogram for predicting the overall survival and cancer-specific survival of leiomyosarcoma patients with lung metastasis

Background

This study sought to assess the prognostic factors for leiomyosarcoma (LMS) patients with lung metastasis and construct web-based nomograms to predict overall survival (OS) and cancer-specific survival (CSS).

Method

Patients diagnosed with LMS combined with lung metastasis between 2010 and 2016 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The patients were randomly divided into a training set and a testing set. The X-tile analysis provides the best age and tumor size cut-off point, and changes continuous variables into categorical variables. The independent prognostic factors were determined by Cox regression analysis, and 2 nomograms were established. Receiver operating characteristic curves and calibration curves were used to evaluate the nomograms. Based on the nomograms, 2 web-based nomograms were established.

Results

Two hundred and twenty-eight cases were included in the OS nomogram construction, and were randomly divided into a training set (n=160) and a validation set (n=68). Age, T stage, bone metastasis, surgery, chemotherapy, marital status, tumor size, and tumor site were found to be correlated with OS. One hundred and eighty-three cases were enrolled in the CSS nomogram construction, and randomly divided into a training set (n=129) and a validation set (n=54). Age, bone metastasis, surgery, chemotherapy, tumor size, and tumor site were found to be correlated with CSS. Two nomograms were established to predict OS and CSS. In the training set, the areas under the curve of the nomogram for predicting 1-, 2-, and 3-year OS were 0.783, 0.830, and 0.832, respectively, and those for predicting 1-, 2-, and 3-year CSS were 0.889, 0.777, and 0.884, respectively. Two web-based nomograms were established to predict OS (https://wenn23.shinyapps.io/lmslmosapp/), and CSS (https://wenn23.shinyapps.io/lmslmcssapp/).

Conclusion

The developed web-based nomogram is a useful tool for accurately analyzing the prognosis of LMS patients with lung metastasis, and could help clinical doctors to make personalized clinical decisions.

Pathological prognostic factors of retroperitoneal liposarcoma: comprehensive clinicopathological analysis of 124 cases

Background

Retroperitoneal liposarcoma (RLS) is a type of rare malignant tumor. The aim of the present study was to study the correlations between the clinicopathological characteristics and the prognostic factors of RLSso as to delineate independent pathological indicators affecting prognosis.

Methods

The RLS pathological specimens were collected at Beijing Shijitan Hospital Affiliated to Capital Medical University from 2008 to 2018, and were used to study the histopathological features, including tumor size, histological types, lymphatic metastasis, tumor emboli in the blood and lymph vessels, and nerve invasion; immunohistochemical features, including Ki-67 and P53 proteins; and molecular pathological features, such as MDM2 (murine double minute2) gene amplification. Clinical treatment and follow-up data were collected, and the survival rate was calculated by Kaplan-Meier method. Univariate and multivariate survival analyses were performed to study the independent pathological factors.

Results

Of the 124 RLS cases, 63 were males (50.8%) and 61 were females (49.2%), with a median age of 52 years (range, 22-80 years). There were 51 cases (41.1%) of well-differentiated liposarcoma, 73 cases (57.3%) of dedifferentiated liposarcoma (DDL); 3 cases (2.4%) with lymph node metastases; 4 cases (3.2%) with tumor emboli in the vessels; 21 cases (16.9%) with Ki-67 label index <20% and 103 cases (83.1%) with Ki-67 label index ≥20%; and 81 cases (65.3%) with P53 <60% and 43 cases (24.7%) with P53 ≥60%. Fluorescence in situ hybridization studies revealed MDM2 gene amplification. Univariate analysis found the following pathological factors were correlated with prognosis: histopathological classification, recurrence, mitosis, tumor necrosis, Ki-67 label index, and P53. Multivariate analysis by Cox proportional hazard model found the following three independent pathological prognostic factors: age [hazard ratio (HR): 1.798, P=0.018], tumor site (HR: 1.263, P=0.002), tumor necrosis (HR: 1.984, P=0.024), and recurrence (HR: 2.161, P=0.049).

Conclusions

Age, tumor necrosis, tumor site, and recurrence could be independent pathological prognostic factors for RLS.

Multi-omics analysis of copy number variations of RNA regulatory genes in soft tissue sarcoma

AIMS

RNA regulatory genes were closely associated with tumorigenesis and prognosis in multiple tumors. Copy number variation (CNV) is a frequent characteristic in soft tissue sarcomas (STS). However, little is known regarding their possible roles in STS.

MAIN METHODS

RNA sequence profiles and CNV data of 255 STS patients were downloaded from the Cancer Genome Atlas (TCGA). The correlation analysis involved CNVs of RNA regulatory genes, patient survival, immune infiltration, and DNA methylation. Drug sensitivity (IC50) was analyzed and validated by MTT assays in STS cell lines.

KEY FINDINGS

CNV events were frequently observed in all kinds (m6A, m5C, ac4C, m1A, m3C, m6Am, m7G, and Ψ) of RNA regulatory genes. Diploid copy number (CN) of METTL4 was associated with better overall survival (OS) in STS and the subtypes (leiomyosarcoma, LMS; dedifferentiated liposarcoma, DDLPS). In STS and LMS, diploid CN of METTL4 was significantly associated with higher infiltration fraction of resting mast cells. In STS and DDLPS, diploid CN of METTL4 possessed lower methylation level in CpG site of cg12105018, which represented better OS. Besides, sensitive drugs for STS cell lines were analyzed according to lower IC50 for the loss CN of METTL4. Temozolomide and Olaparib were identified. Further validation by MTT assays demonstrated that GCT was the most sensitive cell line to both Temozolomide and Olaparib.

SIGNIFICANCE

CNV of METTL4 could be a prognostic biomarker for STS by potentially influencing mast cell infiltration and DNA methylation. Besides, STS with loss CN of METTL4 would be sensitive to Temozolomide and Olaparib.

Nomogram for predicting the overall survival and cancer-specific survival of patients with extremity liposarcoma: a population-based study

BACKGROUND

Extremity liposarcoma represents 25% of extremity soft tissue sarcoma and has a better prognosis than liposarcoma occurring in other anatomic sites. The purpose of this study was to develop two nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of patients with extremity liposarcoma.

METHODS

A total of 2170 patients diagnosed with primary extremity liposarcoma between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were performed to explore the independent prognostic factors and establish two nomograms. The area under the curve (AUC), C-index, calibration curve, decision curve analysis (DCA), Kaplan-Meier analysis, and subgroup analyses were used to evaluate the nomograms.

RESULTS

Six variables were identified as independent prognostic factors for both OS and CSS. In the training cohort, the AUCs of the OS nomogram were 0.842, 0.841, and 0.823 for predicting 3-, 5-, and 8-year OS, respectively, while the AUCs of the CSS nomogram were 0.889, 0.884, and 0.859 for predicting 3-, 5-, and 8-year CSS, respectively. Calibration plots and DCA revealed that the nomogram had a satisfactory ability to predict OS and CSS. The above results were also observed in the validation cohort. In addition, the C-indices of both nomograms were significantly higher than those of all independent prognostic factors in both the training and validation cohorts. Stratification of the patients into high- and low-risk groups highlighted the differences in prognosis between the two groups in the training and validation cohorts.

CONCLUSION

Age, sex, tumor size, grade, M stage, and surgery status were confirmed as independent prognostic variables for both OS and CSS in extremity liposarcoma patients. Two nomograms based on the above variables were established to provide more accurate individual survival predictions for extremity liposarcoma patients and to help physicians make appropriate clinical decisions.