Characterization of natural killer and cytotoxic T-cell immune infiltrates in pancreatic ductal adenocarcinoma.

BACKGROUND AND OBJECTIVES: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor response to systemic therapies, including immunotherapy. Given the immunotherapeutic potential of natural killer (NK) cells, we evaluated intratumoral NK cell infiltrates along with cytotoxic T cells in PDAC to determine their association with patient outcomes. METHODS: We analyzed tumors from 93 PDAC patients treated from 2012 to 2020. Predictor variables included tumor-infiltrating lymphocytes (TILs), T-cell markers (CD3, CD8, CD45RO), NK marker (NKp46), and NK inhibitory marker (major histocompatibility complex class I [MHC-I]) by immunohistochemistry. Primary outcome variables were recurrence-free survival (RFS) and overall survival (OS). RESULTS: Mean TILs, CD3, and NKp46 scores were 1.3 ± 0.63, 20.6 ± 17.5, and 3.1 ± 3.9, respectively. Higher expression of CD3 and CD8 was associated with higher OS, whereas NK cell infiltration was not associated with either RFS or OS. There was a tight positive correlation between MHC-I expression and all T-cell markers, but not with NKp46. CONCLUSIONS: Overall NK cell infiltrates were low in PDAC and did not predict clinical outcomes, whereas T-cell infiltrates did. Further characterization of the immune infiltrate in PDAC, including inhibitory signals and suppressive cell types, may yield better biomarkers of prognosis and immune targeting in this refractory disease.

Low-Dose Sorafenib Promotes Cancer Stem Cell Expansion and Accelerated Tumor Progression in Soft Tissue Sarcomas.

The cancer stem cell (CSC) hypothesis postulates that heterogeneous human cancers harbor a population of stem-like cells which are resistant to cytotoxic therapies, thus providing a reservoir of relapse following conventional therapies like chemotherapy and radiation (RT). CSCs have been observed in multiple human cancers, and their presence has been correlated with worse clinical outcomes. Here, we sought to evaluate the impact of drug dosing of the multi-tyrosine kinase inhibitor, sorafenib, on CSC and non-CSCs in soft tissue sarcoma (STS) models, hypothesizing differential effects of sorafenib based on dose and target cell population. In vitro, human cancer cell lines and primary STS from surgical specimens were exposed to escalating doses of sorafenib to determine cell viability and expression of CSC marker aldehyde dehydrogenase (ALDH). In vivo, ALDHbright CSCs were isolated, exposed to sorafenib, and xenograft growth and survival analyses were performed. We observed that sarcoma CSCs appear to paradoxically respond to the tyrosine kinase inhibitor sorafenib at low doses with increased proliferation and stem-like function of CSCs, whereas anti-viability effects dominated at higher doses. Importantly, STS patients receiving neoadjuvant sorafenib and RT on a clinical trial (NCT00864032) showed increased CSCs post therapy, and higher ALDH scores post therapy were associated with worse metastasis-free survival. These data suggest that low-dose sorafenib may promote the CSC phenotype in STS with clinically significant effects, including increased tumor growth and higher rates of metastasis formation in sarcoma patients.

Langerhans cell histiocytosis with aneurysmal bone cyst-like changes: a case-based literature review.

BACKGROUND: Langerhans cell histiocytosis (LCH) is a neoplastic transformation of myeloid precursors that commonly presents as an osteolytic lesion of the long or flat bones in children. Aneurysmal bone cysts (ABC) are benign neoplasms that frequently affect the metaphysis of long bones and the spine, often revealing a rapidly expansile lesion with fluid-fluid levels. LCH with secondary ABC-like changes is a rare condition that has only been reported five times, with two presentations in the cranium. The aim of this paper is to review the etiology, clinical and radiographic presentations, and treatment of this condition, as well as to present a novel case on the topic. CASE DESCRIPTION: We describe a 5-year-old boy with a rapidly growing head mass and eye pain resulting in a diagnosis of LCH with secondary ABC-like changes. Radiography demonstrated an expansile, lytic lesion of the left parietal bone with fluid-fluid levels. A confirmatory diagnosis was made through histopathology, demonstrating an inflammatory, histiocytic infiltrate staining positive for CD1a, CD68, CD207 (Langerin), and S-100. The lesion was surgically excised, and the patient recovered without any complications. CONCLUSION: We present a novel case of LCH with secondary ABC-like changes managed with surgical excision. While a radiographic workup with multiple imaging modalities is helpful for diagnosis, a thorough immunohistochemical analysis is essential as imaging characteristics are variable and nonspecific. Furthermore, surgical excision should be considered first-line treatment for lesions involving the skull in surgically accessible areas as it is curative, alleviates symptoms, and allows for histopathological diagnosis.

AI-Based Automated Lipomatous Tumor Segmentation in MR Images: Ensemble Solution to Heterogeneous Data.

Deep learning (DL) has been proposed to automate image segmentation and provide accuracy, consistency, and efficiency. Accurate segmentation of lipomatous tumors (LTs) is critical for correct tumor radiomics analysis and localization. The major challenge of this task is data heterogeneity, including tumor morphological characteristics and multicenter scanning protocols. To mitigate the issue, we aimed to develop a DL-based Super Learner (SL) ensemble framework with different data correction and normalization methods. Pathologically proven LTs on pre-operative T1-weighted/proton-density MR images of 185 patients were manually segmented. The LTs were categorized by tumor locations as distal upper limb (DUL), distal lower limb (DLL), proximal upper limb (PUL), proximal lower limb (PLL), or Trunk (T) and grouped by 80%/9%/11% for training, validation and testing. Six configurations of correction/normalization were applied to data for fivefold-cross-validation trainings, resulting in 30 base learners (BLs). A SL was obtained from the BLs by optimizing SL weights. The performance was evaluated by dice-similarity-coefficient (DSC), sensitivity, specificity, and Hausdorff distance (HD95). For predictions of the BLs, the average DSC, sensitivity, and specificity from the testing data were 0.72 [Formula: see text] 0.16, 0.73 [Formula: see text] 0.168, and 0.99 [Formula: see text] 0.012, respectively, while for SL predictions were 0.80 [Formula: see text] 0.184, 0.78 [Formula: see text] 0.193, and 1.00 [Formula: see text] 0.010. The average HD95 of the BLs were 11.5 (DUL), 23.2 (DLL), 25.9 (PUL), 32.1 (PLL), and 47.9 (T) mm, whereas of SL were 1.7, 8.4, 15.9, 2.2, and 36.6 mm, respectively. The proposed method could improve the segmentation accuracy and mitigate the performance instability and data heterogeneity aiding the differential diagnosis of LTs in real clinical situations.

Machine learning for rhabdomyosarcoma histopathology.

Correctly diagnosing a rare childhood cancer such as sarcoma can be critical to assigning the correct treatment regimen. With a finite number of pathologists worldwide specializing in pediatric/young adult sarcoma histopathology, access to expert differential diagnosis early in case assessment is limited for many global regions. The lack of highly-trained sarcoma pathologists is especially pronounced in low to middle-income countries, where pathology expertise may be limited despite a similar rate of sarcoma incidence. To address this issue in part, we developed a deep learning convolutional neural network (CNN)-based differential diagnosis system to act as a pre-pathologist screening tool that quantifies diagnosis likelihood amongst trained soft-tissue sarcoma subtypes based on whole histopathology tissue slides. The CNN model is trained on a cohort of 424 centrally-reviewed histopathology tissue slides of alveolar rhabdomyosarcoma, embryonal rhabdomyosarcoma and clear-cell sarcoma tumors, all initially diagnosed at the originating institution and subsequently validated by central review. This CNN model was able to accurately classify the withheld testing cohort with resulting receiver operating characteristic (ROC) area under curve (AUC) values above 0.889 for all tested sarcoma subtypes. We subsequently used the CNN model to classify an externally-sourced cohort of human alveolar and embryonal rhabdomyosarcoma samples and a cohort of 318 histopathology tissue sections from genetically engineered mouse models of rhabdomyosarcoma. Finally, we investigated the overall robustness of the trained CNN model with respect to histopathological variations such as anaplasia, and classification outcomes on histopathology slides from untrained disease models. Overall positive results from our validation studies coupled with the limited worldwide availability of sarcoma pathology expertise suggests the potential of machine learning to assist local pathologists in quickly narrowing the differential diagnosis of sarcoma subtype in children, adolescents, and young adults.

Surgical and oncologic outcomes following arterial resection and reconstruction for advanced solid tumors.

BACKGROUND AND OBJECTIVES: Although arterial involvement for advanced tumors is rare, vascular resection may be indicated to achieve complete tumor resection. Given the potential morbidity of this approach, we sought to evaluate perioperative outcomes, vascular graft patency, and survival among patients undergoing tumor excision with en bloc arterial resection and reconstruction. METHODS: From 2010 to 2020, we identified nine patients with tumors encasing or extensively abutting major arterial structures for whom en bloc arterial resection and reconstruction was performed. RESULTS: Mean age was 53 ± 20 years, and 89% were females. Diagnoses were primary sarcomas (5), recurrent gynecologic carcinomas (3), and benign retroperitoneal fibrosis (1). Tumors involved the infrarenal aorta (2), iliac arteries (6), and superficial femoral artery (1). Three patients (33%) had severe perioperative morbidity (Grade III + ) with no mortality. At a median follow-up of 23 months, eight patients (89%) had primary graft patency, and five patients (56%) had no evidence of disease. CONCLUSIONS: Arterial resection and reconstruction as part of the multimodality treatment of regionally advanced tumors is associated with acceptable short- and long-term outcomes, including excellent graft patency. In appropriately selected patients, involvement of major arterial structures should not be viewed as a contraindication to attempted curative surgery.

Radiotherapy is Associated With Improved Survival in Patients With Synovial Sarcoma Undergoing Surgery: A National Cancer Database Analysis.

BACKGROUND: Previous studies have demonstrated an association of perioperative radiotherapy (RT) with improved survival in patients with synovial sarcoma (SS) undergoing surgery, but the mechanism for this is unknown. In this study, we sought to further analyze this association using a hospital-based data set where data on chemotherapy administration and surgical margin status are available. METHODS: Using the National Cancer Database, we identified 1216 patients with SS (aged ≥18 y) from 2004-2012 undergoing surgery. Cox proportional hazards analysis was used to study the effect of clinicopathologic variables on overall survival (OS). RESULTS: Mean age at diagnosis was 41.5 y (range 18-90), and 71.3% of tumors were high grade; 22.9% underwent surgery alone, 59.6% received RT with surgery, 44.2% received chemotherapy with surgery, and 26.3% received trimodality therapy. Age, sex, grade, Charlson-Deyo score, and RT (hazard ratio, 0.676; 95% confidence interval, 0.519-0.880; P = 0.004) were associated with improved OS, whereas chemotherapy (hazard ratio, 1.20; 95% confidence interval, 0.899-1.60; P = 0.217) and surgical margin status were not. Trimodality therapy with surgery, RT, and chemotherapy was associated with improved OS when compared with therapy with surgery and chemotherapy alone. CONCLUSIONS: In patients with SS undergoing surgery, we observed a significant improved association of OS with the addition of RT when adjusting for comorbidity score, margin status, and receipt of chemotherapy. These data further support routine implementation of RT in the treatment of patients with SS, including those receiving aggressive multimodality and trimodality care.

Tonsillar Kaposi sarcoma in a renal transplant patient.

Kaposi sarcoma (KS) is a vascular neoplasm caused by human herpesvirus-8 (HHV-8) infection. KS is most often seen in individuals with acquired immunodeficiency syndrome but can occur in patients who are on immunosuppressive therapy. While the skin and oral mucosa are the typical sites for KS, lesions of the tonsil are quite rare with only a few reported cases. Here, we present a case of tonsillar KS occurring in a renal transplant patient. He presented with dysphagia, odynophagia, and weight loss. Oral examination revealed tonsillar hypertrophy with purple discoloration. Imaging revealed diffuse enlargement of Waldeyer's ring with enlarged right cervical lymph nodes, worrisome for post-transplant lymphoproliferative disorder. Microscopic examination of the tonsillectomy specimen showed a vascular proliferation positive for HHV-8, consistent with KS. The patient was subsequently treated with immunosuppression reduction and the addition of sirolimus, which resulted in complete resolution of oropharyngeal and cervical lesions.

Qualitative evaluation of MRI features of lipoma and atypical lipomatous tumor: results from a multicenter study.

OBJECTIVES: The objectives of the study are (1) to distinguish lipoma (L) from atypical lipomatous tumor (ALT) using MRI qualitative features, (2) to assess the value of contrast enhancement, and (3) to evaluate the reproducibility and confidence level of radiological readings. MATERIALS AND METHODS: Patients with pathologically proven L or ALT, who underwent MRI within 3 months from surgical excision were included in this retrospective multicenter international study. Two radiologists independently reviewed MRI centrally. Impressions were recorded as L or ALT. A third radiologist was consulted for discordant readings. The two radiologists re-read all non-contrast sequences; impression was recorded; then post-contrast images were reviewed and any changes were recorded. RESULTS: A total of 246 patients (135 females; median age, 59 years) were included. ALT was histopathologically confirmed in 70/246 patients. In multivariable analysis, in addition to the lesion size, deep location, proximal lower limb lesions, demonstrating incomplete fat suppression, or increased architectural complexity were the independent predictive features of ALT; but not the contrast enhancement. Post-contrast MRI changed the impression in a total of 5 studies (3 for R1 and 4 for R2; 2 studies are common); all of them were incorrectly changed from Ls to ALTs. Overall, inter-reader kappa agreement was 0.42 (95% CI 0.39-0.56). Discordance between the two readers was statistically significant for both pathologically proven L (p < 0.001) and ALT (p = 0.003). CONCLUSION: Most qualitative MR imaging features can help distinguish ALTs from BLs. However, contrast enhancement may be limited and occasionally misleading. Substantial discordance on MRI readings exists between radiologists with a relatively high false positive and negative rates.

Impact of pre-analytical variables on deep learning accuracy in histopathology.

AIMS: Machine learning (ML) binary classification in diagnostic histopathology is an area of intense investigation. Several assumptions, including training image quality/format and the number of training images required, appear to be similar in many studies irrespective of the paucity of supporting evidence. We empirically compared training image file type, training set size, and two common convolutional neural networks (CNNs) using transfer learning (ResNet50 and SqueezeNet). METHODS AND RESULTS: Thirty haematoxylin and eosin (H&E)-stained slides with carcinoma or normal tissue from three tissue types (breast, colon, and prostate) were photographed, generating 3000 partially overlapping images (1000 per tissue type). These lossless Portable Networks Graphics (PNGs) images were converted to lossy Joint Photographic Experts Group (JPG) images. Tissue type-specific binary classification ML models were developed by the use of all PNG or JPG images, and repeated with a subset of 500, 200, 100, 50, 30 and 10 images. Eleven models were generated for each tissue type, at each quantity of training images, for each file type, and for each CNN, resulting in 924 models. Internal accuracies and generalisation accuracies were compared. There was no meaningful significant difference in accuracies between PNG and JPG models. Models trained with more images did not invariably perform better. ResNet50 typically outperformed SqueezeNet. Models were generalisable within a tissue type but not across tissue types. CONCLUSIONS: Lossy JPG images were not inferior to lossless PNG images in our models. Large numbers of unique H&E-stained slides were not required for training optimal ML models. This reinforces the need for an evidence-based approach to best practices for histopathological ML.

Morbidity, mortality and temporal trends in the surgical management of retroperitoneal sarcoma: An ACS-NSQIP follow up analysis.

BACKGROUND: Calls for multivisceral resection (MVR) of retroperitoneal sarcoma (RPS) are increasing, although the risks and benefits remain controversial. We sought to analyze current 30-day morbidity and mortality rates, and trends in utilization of MVR in a national database. METHODS: Overall morbidity, severe morbidity, mortality rates, and temporal trends were analyzed utilizing the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP). RESULTS: From 2012 to 2015, a total of 564 patients underwent RPS resection with 233 patients (41%) undergoing MVR. The MVR group had a higher rate of preoperative weight loss and larger tumors overall. When comparing MVR to non-MVR, there was no significant difference in overall morbidity (22% vs 17%, P = .13), severe morbidity (11% vs 8%, P = .18), or mortality (<1% vs 2%, P = .25). On multivariate analysis, MVR was not associated with increased overall morbidity or severe morbidity. Mortality rates were too low for meaningful statistical analysis. Annual rates of MVR ranged from 37% to 46% with no significant change over time (P = .47). RESULTS: Short-term morbidity and mortality rates after MVR for RPS remain acceptable, but rates of MVR show little change over time in NSQIP hospitals. Concerns about increased morbidity and mortality should not be viewed as a contraindication to wider implementation of MVR for RPS.

Alterations in cancer stem-cell marker CD44 expression predict oncologic outcome in soft-tissue sarcomas.

BACKGROUND: Cancer stem cells (CSCs) have been shown to resist chemotherapy and promote metastasis after cytotoxic therapies. We sought to determine if the expression of CSC markers (aldehyde dehydrogenase [ALDH], CD44, and epidermal growth factor receptor [EGFR]) predicted outcomes in soft-tissue sarcoma (STS) patients. METHODS: We queried an institutional database of 23 STS patients and evaluated immunohistochemical expression of CSC markers ALDH, CD44, and EGFR. The Cancer Genome Atlas (TCGA) was also queried for STS clinical and genomic data. Disease-specific (DSS) and overall survival (OS) were assessed by univariate and Kaplan-Meier analysis. RESULTS: Of the 23 institutional patients, the majority was female, had high-grade tumors and had extremity tumors. With a median follow-up of 27 months, nine patients (39%) experienced distant recurrence, and four (17%) died of disease. Mean H-scores at diagnosis (±standard error of the mean) for CD44, ALDH1, and EGFR were 169 ± 27, 77 ± 15, and 144 ± 23, respectively. On univariate analysis, there was a trend for increased CD44 score to predict both worse DSS and OS (hazard ratio = 1.01, 95% confidence interval 1-1.02, P = 0.056), whereas ALDH and EGFR scores did not. Analysis of 74 TCGA STS cases with complete clinical and genomic data revealed that CD44 copy number alterations predicted worse DSS (9.89 months versus 72.5 months, P = 0.007) and a trend for worse OS (14.03 months versus 38.6 months, P = 0.12), whereas ALDH1 and EGFR copy number alteration did not. Multivariate analysis of the combined data sets was consistent with worse DSS among patients with higher CD44 expression. CONCLUSIONS: Institutional and national TCGA data show the association of elevated baseline CD44 expression with worse STS outcomes. Further study of CD44 as a possible novel STS biomarker appears indicated.

Neoadjuvant Radiotherapy is Associated with R0 Resection and Improved Survival for Patients with Extremity Soft Tissue Sarcoma Undergoing Surgery: A National Cancer Database Analysis.

BACKGROUND: Neoadjuvant radiotherapy (RT) is increasingly advocated for the management of soft tissue sarcoma (STS). Therefore, this study sought to characterize the impact of neoadjuvant RT on rates of R0 resection and overall survival (OS) in extremity STS patients undergoing surgery. METHODS: From January 2003 to December 2012, the study identified patients with a diagnosis of extremity STS from the National Cancer Database. After exclusion of patients younger than 18 years, not treated by surgery, who had metastases at diagnosis, intraoperative RT, and missing or unknown data, 27,969 patients were identified. Logistic regression and Cox-proportional hazard analysis were used to compare rates of R0 resection among preoperative, postoperative, and no-RT cohorts and to determine predictors of R0 resection and OS. RESULTS: The mean age of the patients was 59.5 ± 17.1 years, and 45.9% were female. The median tumor size was 10.5 cm. The data showed that 51% of the patients did not receive RT, 11.8% received preoperative RT, and 37.2% received postoperative RT. The rates of R0 resection were 90.1% for the preoperative RT cohort, 74.9% for the postoperative RT cohort, and 79.9% for the no-RT cohort (P < 0.001). The independent predictors for achievement of R0 resection included academic facility type (odds ratio [OR] 1.36; 95% confidence interval [CI] 1.20-1.55), histologic subtype, tumor size (OR 0.99; 95% CI 0.99-0.99), Charlson score (OR 0.92; 95% CI 0.84-0.99), and preoperative RT (OR 1.83; 95% CI 1.61-2.07). Both R0 resection and RT (pre- or post-operative) were associated with increased OS. CONCLUSIONS: Preoperative RT independently predicts higher rates of R0 resection for patients with extremity STS undergoing surgical resection. Negative surgical margins and pre- or postoperative RT are associated with improved OS.

Osteochondroma-like parosteal osteosarcoma: A case highlighting diagnostic challenge and surgical advances.

Parosteal osteosarcomas are uncommon malignant bone tumors that arise from the bone surface. Their heterogenous components can present challenges in diagnosis. We present a case of a rare variant of this tumor known as an osteochondroma-like parosteal osteosarcoma, which was initially misdiagnosed as a cartilaginous tumor on core needle biopsy. Surgical resection of the tumor ultimately allowed for definitive diagnosis. Our case demonstrates the limitations of needle biopsy in diagnosing variants of parosteal osteosarcoma and the vital role of multidisciplinary discussions in guiding diagnosis and treatment. Furthermore, our case utilizes 3-dimensional printing technology in the surgical treatment, and illustrates the recent advances in patient-specific surgical techniques.

Effect of ALDH1A1 and CD44 on Survival and Disease Recurrence in Patients With Osteosarcoma.

PURPOSE: Emerging evidence suggests that osteosarcoma stem cells (OSCs) may be responsible for tumor initiation propagation, recurrence, and resistance to therapy. We set out to evaluate the relationship between the abundance of ALDH1A1 and CD44-positive cells in biopsy and resection samples on disease recurrence and overall survival. METHODS: A retrospective review of 20 patients, including biopsy and resection samples, was performed at a comprehensive cancer center. Additionally, we queried the publicly available TARGET dataset of osteosarcoma patients. RESULTS: Neither the percentages of ALDH1A1-positive cells nor CD44-positive cells were significantly associated with overall mortality or disease recurrence in either biopsy or resection samples. Unlike our institutional data, overall survival was significantly correlated to higher ALDH1A1 expression in the TARGET dataset both in univariate and age-adjusted analyses. CONCLUSIONS: ADLH1 and CD44, potential markers of OSCs, were not found to be reliable clinical immunohistochemical prognostic markers for osteosarcoma patient survival, specifically disease-free survival. Osteosarcoma patients with high ALDH1A1 RNA expression showed improved overall survival in examining a national genomic database of osteosarcoma patients but again no association with disease-free survival. The potential of CD44 and ALDH1A1 as cellular-specific prognostic markers of survival, and as possible molecular targets, may be limited in osteosarcoma.

Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling.

Objective and Impact Statement: Human epidermal growth factor receptor 2 (HER2) is a critical protein in cancer cell growth that signifies the aggressiveness of breast cancer (BC) and helps predict its prognosis. Here, we introduce a deep learning-based approach utilizing pyramid sampling for the automated classification of HER2 status in immunohistochemically (IHC) stained BC tissue images. Introduction: Accurate assessment of IHC-stained tissue slides for HER2 expression levels is essential for both treatment guidance and understanding of cancer mechanisms. Nevertheless, the traditional workflow of manual examination by board-certified pathologists encounters challenges, including inter- and intra-observer inconsistency and extended turnaround times. Methods: Our deep learning-based method analyzes morphological features at various spatial scales, efficiently managing the computational load and facilitating a detailed examination of cellular and larger-scale tissue-level details. Results: This approach addresses the tissue heterogeneity of HER2 expression by providing a comprehensive view, leading to a blind testing classification accuracy of 84.70%, on a dataset of 523 core images from tissue microarrays. Conclusion: This automated system, proving reliable as an adjunct pathology tool, has the potential to enhance diagnostic precision and evaluation speed, and might substantially impact cancer treatment planning.

Synchronous Undetected HPV+ Cancer in a HPV- Tongue Cancer Patient.

We report a case of a 63-year-old male who presented with synchronous pT1N1 p16-positive squamous cell carcinoma (SCC) of the left tonsil and pT4N0 p16-negative SCC of the left tongue.

Coccidioidomycosis in Joint Replacement: A Review of the Literature With Case Presentations.

Coccidioidomycosis is a fungal infection endemic to certain regions of the Americas. In some cases, the organism may infect the musculoskeletal system, resulting in a prosthetic joint infection (PJI). Due to its difficulty in diagnosis, treatment of coccidioidomycosis in PJI is often delayed. Furthermore, with limited number of case reports, a standard of care in treatment has yet to be established. We present 2 cases of coccidioidomycosis PJI, the extensive evaluation that led to the diagnosis, and the treatment provided. This report highlights the natural progression of coccidioidomycosis in a prosthetic joint, the diagnostic features including histology, advanced imaging, and final treatment administered.

Intratumoral NKp46+ natural killer cells are spatially distanced from T and MHC-I+ cells with prognostic implications in soft tissue sarcoma.

Introduction: Soft tissue sarcomas (STS) are rare, heterogenous malignancies with an unmet need for novel immunotherapies. Tumor infiltrating lymphocytes (TILs) have been linked with favorable outcomes in STS patients, though the contribution of natural killer (NK) cells and spatial relationships of TILs with MHC-I expressing cells lacks detailed characterization. Experimental design: Using archived and prospectively collected specimens, we evaluated intratumoral NK cells by immunohistochemistry (IHC), flow cytometry, and immunofluorescence (IF). We assessed spatial localization of NK and T cells by multiplex IF, analyzing the effects of MHC-I expression status on NK and T cell clustering. Results: Both intratumoral NKp46 and CD56dim expression were associated with significantly improved overall survival (P=0.05), while higher infiltrates of CD56bright NK cells predicted a worse prognosis (P=0.05). The presence of intratumoral NK cells was inversely proportional to CD3+ T cells. Spatial analyses showed NK cells preferentially clustering close to other NK cells with sparse CD3+ T and CD8+ T cells in range (P<0.0001). Additionally, CD3+ T and CD8+ T cells showed significantly greater co-localization with MHC-I+ cells, compared to NK cells (P<0.0001). After neoadjuvant radiotherapy, there was greater CD8 clustering, while after neoadjuvant chemotherapy, there was overall lower TIL clustering. Conclusion: Intratumoral NK cells are prognostic in STS and localize closer to MHC-I- cells than T cells. Although both NK and T cells are associated with improved survival in STS, their differential distribution in the TME based on MHC-I expression status may serve as a biomarker for improved immunotherapy treatment selection.